YANNOU Bernard

Technology Transfer (TT) is well recognized as one of the most important means to enhance innovative capabilities within firms. However, transferring technology is a complex process resulting from actions taken by various actors and organizations. In addition, when transfer actions occur, very often participants do not label it as technology transfer which makes it difficult to study. Many models describe the technology transfer process. Some models consider this process as a linear progression of steps. This process begins with idea generation and technology development at the university in order to establish a university-private firm relationship through a formal research agreement. Some models describe technology transfer as networking arrangements between two parties without relevant formal research. Others are based on the 'broadcasting analogy' where the technology to be transferred is assimilated to be a radio transmitted message. Based on a comprehensive literature analysis of existing technology transfer models and a long-term field observation of five transfer projects, this paper proposes one conceptual model for a better understanding of the technology transfer process between a Technology Transfer Center (TTC) and Small and Mediumsized Enterprise (SME). The model describes the stages of the technology transfer project from the step one of making contact to the step five of adoption. Based on five in-depth technology transfer projects analysis, this paper highlights the dynamic of a TT project by applying the proposed model.

No summary available.

Designing and managing system transitions towards sustainable urban futures are crucial to fulfilling the Paris Agreement and the United Nations (UN) Sustainable Development Goals (SDGs). However, the complexity and multidisciplinarity of urban systems pose challenges to the holistic conceptualisation, design, and management of such transitions. Utilising complex system theory as the theoretical foundation, we apply transition concepts from Complex Adaptive Systems (CAS), Multi-Level Perspective (MLP), Social Practice Theory (SPT), and Future Scenario Methods (FSM) to explore the frameworks’ potentials and shortcomings when applied to the urban mobility system transition (UMST) of Paris and its region Île-de-France (ÎdF) between 2001 and 2021. Our leading and supporting research questions are: RQ1: To what extent can current transition frameworks represent the UMST? RQ1a: What are the key transition drivers (TD) of Paris’ UMST between 2001 and 2021? RQ1b: What are the key transition frameworks that have been applied to UMST? RQ1c: How adequately can these frameworks represent the UMST of Paris? To answer these questions, we introduce the challenge and the underlying complex system theory, followed by the case study description. Afterwards, each framework is described, applied to the case, and discussed. This is followed by a literature-driven analysis and discussion of complements, commonalities, and mismatches between the frameworks. Finally, the initial outcomes are discussed, and a perspective for the next steps building on this preparatory work is drawn. Key outcomes of the paper are: • A descriptive case study of the UMST of Paris between 2001 and 2021. • An interdisciplinary overview of UMST frameworks applied to the case study. • A discussion of complementary, overlapping, and competing properties of the transition frameworks that will feed the next steps of the research towards the development of a holistic, heuristic transition framework for UMST.

A refrigerant system (like that of a supermarket) is a complex system if we consider all the stakeholders throughout its lifecycle phases (use, maintenance, technological update, end of life). The lack of stakeholders' interaction during the design and other lifecycle stages of such a system generates issues and leads to sub-optimal system performances. We used the RID methodology to identify the main areas for improvement for these activities related to the refrigerant system. It is precisely designed to analyze, within the scope of activity, the major stakeholders' problems (user profiles) during lifecycle phases (use situations) to deduce areas for improvement (value buckets). Therefore, we built a process of interviews and data collection on existing practices to feed into a RID model. The first results are an archetypal description of the actors and problems encountered according to the lifecycle phases. The second part is a prioritized mapping of the areas to improve despite a certain number of known available solutions but proven insufficient.

Abstract Most services and products are designed in response to the needs, desires or expectations of humans. A variety of methodologies grouped by the term Human-Centred Design (HCD) have been deployed to formalise and improve this process, ranging from user-centred to participatory practices. However, the approaches’ consideration is primarily limited to individuals in their respective space and time. To examine these system boundaries in detail and address potentials for adaptation, this paper reviews dominant HCD methodologies, categorises them and highlights their respective characteristics. Further, concepts and methodologies from related fields are studied for potential contributions to HCD. This results in a proposed re-definition of the system boundaries of HCD by integrating spatio-temporal impacts on humans through an extended social, environmental and economic scope. The different studied approaches and varying impact assessments are exemplarily applied to the case study of urban mobility, in particular human-centred, scenario-based design approaches. However, the described methods and concepts are kept generic to ensure the applicability across various domains of design practice.

Due to recent technological advancements, automation and autonomous solutions are gaining increasing popularity. Yet, a lack of in-depth investigations is noticed on the potential environmental benefits and economic repercussions of implementing autonomous systems. The present study aims to fill part of this gap by quantifying the environmental and economic sustainability of a robotic lawn mower, in comparison with human-operated counterparts. Combining life cycle assessment and life cycle costing methodologies, and by defining adequate functional units, building simulation models, and collecting life cycle inventory data, a systematic comparative study between autonomous and conventional lawn mowers is performed on their environmental and economic impacts. Through this multi-indicator analysis, environmental and economic trade-offs between the autonomous and conventional mowing solutions are quantitatively discussed for key relevant usage scenarios, from mowing an average residential yard to maintaining larger fields like a football stadium or a schoolyard. Concretely, sensitivity analyses on key parameters influencing the performance of the autonomous mower have been conducted to evaluate the environmental and economic benefits of an augmented robotic mower. While optimising the path planning of the current robotic mower would lead to the most substantial savings, improvements on the battery performance, cutting width, and speed of the autonomous solution appear as other promising areas for future work.

Implementing circular economy (CE) practices can lead to both environmental savings and competitive advantages for companies. While transitioning from a linear production system to a closed-loop system is not straightforward, adequate methodology and tools can support industrialists in this sustainable shift. This paper proposes a multi-tool approach to systematically identify, classify, and assess the contribution of influence parameters and action levers to close the loop on products and key materials. Industrial ecology and model-based engineering tools are combined to ensure a systemic analysis and evaluation. The developed multi-tool approach combines, in a stepwise methodology, material flow analysis, fuzzy cognitive mapping, structural analysis, and system dynamics, to model and qualify the impact of potential and promising CE strategies. To illustrate each step of this multi-tool methodology, a case study is carried out on a real-world industrial product: a catalytic converter, which contains a non-negligible amount of platinum, considered as a critical raw material by the European Commission. New insights to close the loop on platinum from catalytic converters are thus provided and discussed. Notably, the connections between key action levers to close the loop on platinum are identified and highlighted, including regulations to limit the number of exports, mandatory recycling and reuse rate, end-users behaviors, based on regulatory constraints and financial motivations, and platinum price fluctuation. These findings could help to generate and fine-tune an ad hoc system dynamics model to evaluate the impact of key action levers through more specific scenarios. For instance, the broader implication of this multi-tool methodology could support an original equipment manufacturer in the evaluation of potential CE strategies, through the simulation of selected action levers on the circularity and sustainability performance of their value chain. Ultimately, it could provide quantitative insights to relevant prospective questions, such as, what if a take-back scheme is proposed to augment the collection rate by a given percentage, or what if the design is modified for easy disassembly.

Serious games (SGs) are motivational and practical pedagogical tools that have been widely used in design education. SGs seem to be an efficient way to give instructions on innovation processes (IPs), offering unique and attractive environments to support situated learning. While there has been much interest in SGs of the IPs type, there is very little research about the design framework to reduce the complexity and time consumption of their design process. This paper presents the preliminary results of our ongoing study: a design framework adapted to innovation SGs. The framework integrates eight general design frameworks/models/methodologies for SGs. Besides, it introduces a new stage "analysis of traditional teaching experience," which conducive to the early phases of the design. We use a case study to prove the value of this stage. First, it aids designers in defining the teaching objectives of innovation SGs, that is, choosing required competencies from innovation competency frameworks. More importantly, it helps identify game mechanics that may contribute to the realization of teaching objectives. This stage should support designers successfully making the transition from traditional innovation teaching towards SGs.

Autonomous systems-such as self-driven tractors, cars, autonomous lawnmowers, or vacuum cleaner-seem to become increasingly attractive and operationally efficient. Yet, the environmental, economic, and social impacts of implementing autonomous solutions, as a substitution to conventional human-operated ones, still need to be quantitatively investigated. This piece of research questions whether existing methods and indicators are satisfactory to compare the performance of autonomous systems with human-operated counterparts through the lens of sustainability? Currently, few integrated approaches are linking environmental life cycle assessment (LCA), life cycle costing, and social-LCA. Also, additional conceptual and methodological issues arise in the case of autonomous systems assessment. As such, activity-based costing can be relevant complementary tool to integrate to ensure that the comparison in terms of sustainability performance of autonomous systems with their conventional counterpart is performed on a sound basis. In this line, this paper proposes the first elements of an integrated framework to guide and compare the life cycle sustainability performance between human-operated systems and newly developed autonomous alternatives.

This paper investigates and questions the relevance of product-centric circularity indicators in a product design context. To do so, reviews of eco-design tools and critical analyses of circularity indicators at the micro level of circular economy implementation are combined with a new workshop experimenting four of these indicators with the aim to improve the circularity performance of an industrial product. On this basis, the four tool-based circularity indicators tested are mapped on the engineering design and development process, and are positioned among the pool of main eco-design tools.

Combining new insights from both bibliometric and text mining analyses, with prior relevant research conversations on circular economy (CE) and industrial ecology (IE), this paper aims to clarify the recent development trends and relations between these concepts, including their representations and applications. On this basis, discussions are made and recommendations provided on how CE and IE approaches, tools, and indicators can complement each other to enable and catalyze a more circular and sustainable development, by supporting sustainable policy-making and monitoring sound CE strategies in industrial practices.

To date, a limited number of in-depth case studies addressing the end-of-life management of heavy vehicles has been reported in the scientific literature. An action research approach is conducted in collaboration with an emerging international remanufacturing center of heavy handling machines to bring a contribution to this gap in a circular economy perspective. This industrial pilot study considers the entire end-of-life management of a whole heavy vehicle, from the dismantling to the recovery of used parts, through remanufacturing. It illustrates as such the multiple dimensions to consider when closing-the-loop on heavy vehicles, namely: technical and organisational knowledge (e.g., infrastructures, tooling, dismantling process and remanufacturing feasibility), as well as economic considerations (e.g., solutions to optimize the value recovered according to market needs, through the identification of potential recovery channels). To do so, a multi-scale modelling is proposed, taking into account: (i) the condition of the used vehicle and residual values of key components, (ii) the dismantling process and capabilities, (iii) the possible end-of-life options and associated market. A first dismantling operation on a worn-out 8-ton forklift truck is performed and closely analyzed to identify hotspots and areas for improvement. Based on that and taking inspiration from the best practices of the automotive recycling sector, a new dismantling process is designed including improvement in terms of organisation, resources used, disassembly time, and comfort for the operator. This new ly proposed process is then tested and validated through a second dismantling experimentation on a similar forklift truck. Moreover, a practical spreadsheet, to be used by the industrialist, is proposed and applied as a decision-making support tool to compare and select the most appropriate end-of-life pathways for recovered components according to the economic aspects of each circular option, among reuse, remanufacturing and material recovery. Eventually, lessons learnt from this industrial case study open up on broader implications and challenges (e.g., the applicability, generalization and scaling-up of commendable practices from one industrial sector to another) to achieve a more advanced circular economy in the heavy vehicle industry.

No summary available.

Ecodesign has gained significant traction in recent years ranging from academic research to business applications at a global scale. Initial emphasis on the environmental aspect of design has evolved to include economic and social aspects, with projects ranging from small-scale products to large-scale industrial systems. In this paper, the authors re-analyse 10 of their major ecodesign research projects of the past ten years to identify five categories of challenges and promising future directions for ecodesign research. This paper is primarily a retrospective position paper based on the authors’ experience of actual design studies, providing also a relevant literature review and summary of design practices.

In France, the building sector accounts for 45% of total energy consumption and nearly a quarter of total CO2 emissions. The effects of climate change and their impact on our model of society are no longer in doubt. However, the sector's response is not up to the challenge. The multiplication of labels, certifications or guarantees, shows a lack of cooperation between the actors. This book demonstrates the urgency of adopting a collective approach - eco-design - that integrates all solutions to control the environmental impacts of buildings. It presents the emerging scientific issues that need to be addressed urgently, organizing them into three main themes: assessment of the value provided, change of scale and occupant involvement. Fifteen professionals from the sector have mobilized in the face of the environmental emergency to lay the foundations for sustainable practices for building actors. This book is the result of a collaborative research project between CentraleSupélec, Vinci Construction, ADEME and the EcoSD network. It is intended to foster research collaborations and to serve as a reflection tool for decision-makers.

While autonomous machines are considered as a new opportunity to augment safety, reliability, productivity, and efficiency, the actual environmental and economic sustainability performances of many autonomous systems remain yet to be quantified. The present research aims to fill part of this gap by evaluating the life cycle impact and cost of autonomous solutions in the agricultural industry. Comparative life cycle assessment (LCA) and life cycle costing (LCC) are carried out on a real-world case study putting in parallel a robotic electric lawn mower (autonomous solution) and conventional-gasoline-and electricity-powered-pushing mowers (human-operated counterparts). Results are interpreted in terms of global warming potential and total cost of ownership. While the autonomous system already appears to be a promising sustainable alternative, discussions and quantitative insights are also provided on the conditions that would lead to further environmental savings and economic profit for this autonomous solution.

Implementing circular economy practices can lead to both environmental savings and competitive advantage for companies. While transitioning from a linear production system to a closed-loop system is not straightforward (Franco, 2019), adequate methodology and tools can support industrialists in this sustainable shift. This research work proposes a multi-tool approach (Figure 1) to systematically identify, classify, and assess the contribution of influence parameters and action levers to close-the-loop on industrial components and critical materials. It combines previous insights from material flow analysis (Figure 2), with new findings from fuzzy cognitive mapping (Figure 3), structural analysis (Figure 4), and system dynamics in a stepwise methodology. A case study is carried out on a real-world industrial product to illustrate each step of the developed methodology.

This study provides insight into traveler-related attributes affecting the choice of future autonomous vehicles (AVs) and explores the importance of integrating those attributes into agent-based simulations and service optimization assessments. For this purpose, an online survey was carried out to collect data on travelers of the greater Paris region along with their behavior regarding autonomous vehicles. In addition, this paper identifies AV taste variations among individuals as well as the subjective criteria behind their willingness-to-use a shared autonomous vehicle (SAV) service depending on their current mode of transport. The paper shows how traveler-related attributes are relevant to studying a shared autonomous mobility system and how they can enhance the accuracy of agent-based models and the traveler preference dimension in optimization models.

No summary available.

Taking into consideration all the life cycle of a product is now an important step in the design of a product or a technology. Despite the improvement in refrigerant regulation, the environmental impacts of refrigeration systems remain important and need to be improved. In this paper, the environmental impacts of refrigeration systems in a typical hypermarket are compared using the LCA methodology under different conditions. The system is used to provide cold at two levels of temperature: medium and low temperature during a life period of 15 years. The most commonly used architectures of hypermarket cold production systems are investigated: centralized direct expansion systems and indirect systems using a secondary loop to transport the cold. The variation of power needed during seasonal changes and during the daily opening/closure periods of the hypermarket are considered. R134a as the primary refrigerant fluid and two types of secondary fluids are considered (liquid CO2 and ammonia). The composition of each system and the leakage rate of the refrigerant through its life cycle are taken from the literature and industrial data. Twelve scenarios are examined. They are based on the variation of three parameters, 1. location: France (Paris), Spain (Toledo) and Sweden (Stockholm), 2. different sources of electric consumption: photovoltaic panels and low voltage electric network and 3. architecture: direct and indirect refrigeration systems. SimaPro software was used to assess the environmental performances and different impact assessment methods were used. CML method is used to evaluate the midpoint environmental indicators and IMPACT 2002+ to assess endpoint indicators. This study highlights the most environmentally damaging parameter to be electric consumption compared to the impacts of refrigerant leakage supporting the conclusions of previous studies. The use of a secondary loop lowers the refrigerant amount in the primary loop and thus the climate change indicator is reduced. The cost estimation of CAPEX and OPEX shows that depending on the location the use of photovoltaic panels can be more expensive and does not bring any improvement in environmental impacts.

This study provides insight into traveler-related attributes affecting the choice of future autonomous vehicles (AVs) and explores the importance of integrating those attributes into agent-based simulations and service optimization assessments. For this purpose, an online survey was carried out to collect data on travelers of the greater Paris region along with their behavior regarding autonomous vehicles. In addition, this paper identifies AV taste variations among individuals as well as the subjective criteria behind their willingness-to-use a shared autonomous vehicle (SAV) service depending on their current mode of transport. The paper shows how traveler-related attributes are relevant to studying a shared autonomous mobility system and how they can enhance the accuracy of agent-based models and the traveler preference dimension in optimization models.

The purpose of this paper is to develop and discuss a framework aiming at monitoring and optimizing the circularity performance of products for ensuring and facilitating green profit design trade-offs whilst meeting or anticipating end-of-life regulations during the design and development process of industrial products. The proposed framework is used to extend the Green Profit Model-an optimization model to maximize the total profit from the sales of new and remanufactured products, while achieving environmental impact savings-by adding a third dimension to this model, which is the circularity performance. As such, in addition to remanufacturing, it covers a wider spectrum of circular economy practices, leading to additional economic opportunities and environmental trade-offs between maintenance, reuse, remanufacturing and recycling at a product, parts and material levels. A first formulation of this extended optimization model is given and discussed through an illustrative example. By connecting the circularity performance of products with possible economic profit and environmental impact savings, it thus contributes in advancing the understanding and linkages in the area of circular design, life cycle analysis, industrial decision-support tool, and environmental regulations. Concretely, practical implications for both design engineering and green policy making are highlighted.

Travelers interact with a large number and variety of products and services during their journeys. The quality of a travel experience depends on a whole urban mobility system considered in space and time. This paper outlines the relevant concepts to be considered in designing urban mobility. The goal is to provide a language and insights for the early stages of a design process. A literature review sheds light on the complexity of urban mobility from technical, socio-technical, and user experience (UX) perspectives. Observations of experiences in urban areas provide data for describing and understanding travel experience patterns and issues. The paper proposes a conceptual model to describe and analyze different facets of traveler experience, and categorizes problems that travelers face when they interact with an urban mobility system. A case study is reported illustrating the use of the conceptual model in identifying travel problems for a demand-responsive transport (DRT) service.

In response to the growing development of a wide variety of circularity indicators (c-indicators), a taxonomy has been developed to gain clarity about their focuses, purposes and possible usages (e.g., benchmarking several circular economy business models, comparing two product designs on their potential circularity performance). The advisor linked to this taxonomy works like an expert system in which eight queries are asked to direct users towards the most appropriate set(s) of circularity indicators. To support the diffusion and usage of this selection tool, it is now accessible through a web-based platform (https://c-indicators.000webhostapp.com/index.php). It is particularly intended to industrial practitioners such as designers, engineers, managers, as well as decision-makers or policy-makers, who want to learn how they could identify and implement suitable circularity indicators (i.e. well-aligned with their needs) in practice in their CE projects. Interestingly, two tutorial videos (one explaining how to use the advisor, and one experiencing it through an industrial case) are also embodied in the web platform (http://www.circulareconomyindicators.com/advisor.php).

This research set out to identify and structure from online reviews the words and expressions related to customers' likes and dislikes to guide product development. Previous methods were mainly focused on product features. However, reviewers express their preference not only on product features. In this paper, based on an extensive literature review in design science, the authors propose a summarization model containing multiples aspects of user preference, such as product affordances, emotions, usage conditions. Meanwhile, the linguistic patterns describing these aspects of preference are discovered and drafted as annotation guidelines. A case study demonstrates that with the proposed model and the annotation guidelines, human annotators can structure the online reviews with high inter-agreement. As high inter-agreement human annotation results are essential for automatizing the online review summarization process with the natural language processing, this study provides materials for the future study of automatization.

Serious games (SGs) as a new educational format have gained interest among many scholars from diverse fields. SGs seem to be useful tools for teaching innovation processes (IP) as they guarantee intrinsic motivation and provide situated learning. So far, there is no guideline on designing IP games and lowering their development time while ensuring their effectiveness. To fill this gap, we should first analyse the existing IP games with evaluation methods and synthesise their commonalities. Numerous methods have been put forward in the literature to assess digital SGs. however, most of the SGs for IP are board games. That is why we explore in this paper the use of Serious Game Design Assessment (SGDA) framework to analyse IP board games. According to the case study on an open innovation board game, we suggest applying this method to examine the a priori relevance of game elements (components that make up a game system). Moreover, we make recommendations to complement the SGDA framework with Game and Learning Mechanics, and real-world information. This contribution should help designers transform traditional educational supports into serious board games for teaching IP.

In a context of transition towards a more circular economy (CE), this study undertakes an analysis of the appropriate transfers and applications of best managerial practices, regulations and know-how from the automotive sector to the heavy vehicle one, as well as from the European Union (EU) to the United States of America (U.S.), and vice versa. While the EU appears to be a few steps ahead of policy activity regarding the management of end-of-life automotive vehicles (Directive 2000/53/EC and Extended Producer Responsibility principles), the U.S. heavy vehicle industry presents several aspirational industrial practices, including the collaboration between end-of-life actors, supporting parts remanufacturing and facilitating reuse. New empirical findings and lessons learned from both geographical regions are combined with previous analyses to develop a benchmarking template of commendable CE practices. Against this background, the findings open on the remaining challenges and circular economy opportunities for both regions, as well as for emerging and newly industrialized countries whose automotive markets are growing fast.

No summary available.

The purpose of this paper is to develop and discuss a framework aiming at monitoring and optimizing the circularity performance of products for ensuring and facilitating green profit design trade-offs whilst meeting or anticipating end-of-life regulations during the design and development process of industrial products. The proposed framework is used to extend the Green Profit Model-an optimization model to maximize the total profit from the sales of new and remanufactured products, while achieving environmental impact savings-by adding a third dimension to this model, which is the circularity performance. As such, in addition to remanufacturing, it covers a wider spectrum of circular economy practices, leading to additional economic opportunities and environmental trade-offs between maintenance, reuse, remanufacturing and recycling at a product, parts and material levels. A first formulation of this extended optimization model is given and discussed through an illustrative example. By connecting the circularity performance of products with possible economic profit and environmental impact savings, it thus contributes in advancing the understanding and linkages in the area of circular design, life cycle analysis, industrial decision-support tool, and environmental regulations. Concretely, practical implications for both design engineering and green policy making are highlighted.

One of the main tasks of today's data-driven design is to learn customers' concerns from the feedback data posted on the internet, to drive smarter and more profitable decisions during product development. Feature-based opinion mining was first performed by the computer and design scientists to analyse online product reviews. In order to provide more sophisticated customer feedback analyses and to understand in a deeper way customer concerns about products, the authors propose an affordance-based online review analysis framework. This framework allows understanding how and in what condition customers use their products, how user preferences change over years and how customers use the product innovatively. An empirical case study using the proposed approach is conducted with the online reviews of Kindle e-readers downloaded from amazon.com. A set of innovation leads and redesign paths are provided for the design of next-generation e-reader. This study suggests that bridging data analytics with classical models and methods in design engineering can bring success for data-driven design.

Around 40% of the platinum used in EU catalytic converters is not recovered for recycling and is therefore 'lost' forever, indicates a new study. A more circular economy for platinum is essential to reduce imports of this critical raw material to the EU and minimise its damaging effects on the environment, the researchers argue. Better collection systems for end-of-life catalytic converters and tighter regulation of waste exports could help close the loop on platinum.

Being able to measure, improve and manage the circularity performance of industrial products is of paramount importance in a period of transition towards more circular industrial practices, in line with sustainable development objectives. However, without a stabilized definition of the circular economy, the number of circularity indicators, of unequal ambitions, is still growing, creating a blur around their proper use and appropriation by industrial practitioners. After highlighting the benefits of using such indicators, a systematic review of 55 sets of indicators leads to a first typology of circularity indicators, thus clarifying their possible uses. Based on this, we propose a set of five circularity indicators to support manufacturers, at a micro level, in their transition to more circular practices. This work suggests future key areas for moving towards a circular economy in an effective, efficient and sustainable way.

No summary available.

Customers post online reviews at any time. With the timestamp of online reviews, they can be regarded as a flow of information. With this characteristic, designers can capture the changes in customer feedback to help set up product improvement strategies. Here we propose an approach for capturing changes of user expectation on product affordances based on the online reviews for two generations of products. First, the approach uses a rule-based natural language processing method to automatically identify and structure product affordances from review text. Then, inspired by the Kano model which classifies preferences of product attributes in five categories, conjoint analysis is used to quantitatively categorize the structured affordances. Finally, changes of user expectation can be found by applying the conjoint analysis on the online reviews posted for two successive generations of products. A case study based on the online reviews of Kindle e-readers downloaded from amazon.com shows that designers can use our proposed approach to evaluate their product improvement strategies for previous products and develop new product improvement strategies for future products.

Designers improve urban mobility solutions by investigating archetypal usage problems in existing mobility systems. User-centred design methods help accomplish this task, but lack effectiveness when not supported by appropriate tools. Here we posit that the use of a traveller-centred stimulus improves the effectiveness of travel problem generation. To test this hypothesis, an experiment is conducted with two control groups as a baseline for non-stimulated problem generation and two experimental groups that are provided with a traveller-centred stimulus. The two sets of groups are composed of one group of urban mobility experts and one group of non-experts. Results show that stimulated groups generate novel ideas with a greater variety covering most of the traveller experience dimensions than non-stimulated groups.

Monitoring properly the circularity performance of technical products is a point of increasing importance. Yet, evaluating the circularity potential of products during (re)design and development phases is a challenging task. In this study, several C-indicators are experienced by doctoral students and industrialists through two workshops on a real-world industrial product. The values obtained for each indicator are collected and analyzed: as all participant are working on the same technical product with the same dataset, the circularity scores calculated are compared to discuss the reliability and the uncertainty related to these indicators. These new empirical insights are put in parallel with the existing critical analyses of C-indicators from literature. As a result, future research directions on circularity indicators are advanced and discussed, including: the integration of uncertainty considerations into the assessment methodology of circularity indicators. the uptake by industry of such indicators during product design and development. the link between circularity and sustainability scores.

Implementing circular economy (CE) principles is increasingly recommended as a convenient solution to meet the goals of sustainable development. New tools are required to support practitioners, decision-makers and policy-makers towards more CE practices, as well as to monitor the effects of CE adoption. Worldwide, academics, industrialists and politicians all agree on the need to use CE-related measuring instruments to manage this transition at different systemic levels. In this context, a wide range of circularity indicators (C-indicators) has been developed in recent years. Yet, as there is not one single definition of the CE concept, it is of the utmost importance to know what the available indicators measure in order to use them properly. Indeed, through a systematic literature review-considering both academic and grey literature-55 sets of C-indicators, developed by scholars, consulting companies and governmental agencies, have been identified, encompassing different purposes, scopes, and potential usages. Inspired by existing taxonomies of eco-design tools and sustainability indicators, and in line with the CE characteristics, a classification of indicators aiming to assess, improve, monitor and communicate on the CE performance is proposed and discussed. In the developed taxonomy including 10 categories, C-indicators are differentiated regarding criteria such as the levels of CE implementation (e.g. micro, meso, macro), the CE loops (maintain, reuse, remanufacture, recycle), the performance (intrinsic, impacts), the perspective of circularity (actual, potential) they are taking into account, or their degree of transversality (generic, sector-specific). In addition, the database inventorying the 55 sets of C-indicators is linked to an Excel-based query tool to facilitate the selection of appropriate indicators according to the specific user's needs and requirements. This study enriches the literature by giving a first need-driven taxonomy of C-indicators, which is experienced on several use cases. It provides a synthesis and clarification to the emerging and must-needed research theme of C-indicators, and sheds some light on remaining key challenges like their effective uptake by industry. Eventually, limitations, improvement areas, as well as implications of the proposed taxonomy are intently addressed to guide future research on C-indicators and CE implementation.

This report provides additional material to the authors' publication "Research perspectives in eco-design" (submitted to Design Science, April 2019). It gives a detailed description of the ten case studies used in the paper to support the authors' analysis and recommendations.

Implementing circular economy (CE) principles is increasingly recommended as a convenient solution to meet the goals of sustainable development. New tools are required to support practitioners, decision-makers and policy-makers towards more CE practices, as well as to monitor the effects of CE adoption. Worldwide, academics, industrialists and politicians all agree on the need to use CE-related measuring instruments to manage this transition at different systemic levels. In this context, a wide range of circularity indicators (C-indicators) has been developed in recent years. Yet, as there is not one single definition of the CE concept, it is of the utmost importance to know what the available indicators measure in order to use them properly. Indeed, through a systematic literature review-considering both academic and grey literature-55 sets of C-indicators, developed by scholars, consulting companies and governmental agencies, have been identified, encompassing different purposes, scopes, and potential usages. Inspired by existing taxonomies of eco-design tools and sustainability indicators, and in line with the CE characteristics, a classification of indicators aiming to assess, improve, monitor and communicate on the CE performance is proposed and discussed. In the developed taxonomy including 10 categories, C-indicators are differentiated regarding criteria such as the levels of CE implementation (e.g. micro, meso, macro), the CE loops (maintain, reuse, remanufacture, recycle), the performance (intrinsic, impacts), the perspective of circularity (actual, potential) they are taking into account, or their degree of transversality (generic, sector-specific). In addition, the database inventorying the 55 sets of C-indicators is linked to an Excel-based query tool to facilitate the selection of appropriate indicators according to the specific user's needs and requirements. This study enriches the literature by giving a first need-driven taxonomy of C-indicators, which is experienced on several use cases. It provides a synthesis and clarification to the emerging and must-needed research theme of C-indicators, and sheds some light on remaining key challenges like their effective uptake by industry. Eventually, limitations, improvement areas, as well as implications of the proposed taxonomy are intently addressed to guide future research on C-indicators and CE implementation.

The development of key skills is becoming a strategic issue that conditions the long-term prosperity of companies. In the academic world, this imperative translates into a double challenge: (1) to identify these key competencies and (2) to enable their acquisition by both students in initial training and by an industrial audience. This study focuses on the description of a repository of radical innovation competencies in support of competency-based learning. We focus in particular on the study of the skills required for an innovation strategy that aims at identifying the needs not covered by existing market solutions through an in-depth investigation of the motivations, mental/emotional state, values and preferences of the end-user: the need seeker strategy. A first phase combining an extensive literature review, interviews with 28 innovation experts/actors and a micro-qualitative study over two sessions (each lasting four months) of radical innovation need seeker training per project. This first study led to the design of a repository of 36 individual, collective and leadership competencies. Based on the results of this first phase, we propose in this article an approach that allows us to translate these competencies into training objectives. The proposed approach aims to contribute to the design of significant and transformative training experiences in support of a need-seeker radical innovation strategy.

No summary available.

Over 50 sets of circularity indicators – created and used by academia, consulting companies and governmental agencies worldwide – have been reviewed and classified into a need-based taxonomy driven by the usage of such indicators. A query tool associated to the proposed taxonomy databank – using MS Excel with macros – has been designed to help identifying the most relevant indicators regarding the user needs. In inputs, eight questions are asked about the: i) scale of measurement. ii) circularity perspective. iii) circularity performance. iv) circularity loop. v) dimensionality. vi) usages and purposes. vii) transversality. viii) type and format. In outputs, appropriate indicators are identified and following information is displayed: a) tool/indicator name. b) working principle. c) systemic level. d) kind of circularity. e) dimensionality and unit. f) data required to compute the indicator.

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Empowering key competencies to support a specific innovation strategy becomes a critical issue to the long term survival of many today's firms. This imperative reflects a challenge for design and innovation education, in properly preparing students. In this article, we present a competency framework to guide the implementation of a competency-based learning of design and innovation. In particular, we focus on skills required to implement an innovation strategy derived by a 'superior end-user understanding' to get first to market, namely the Need-Seeker Strategy. Our methodology combines an extensive literature review, an empirical study on project-based learning and expert interviews to result in an original competency framework supporting the need-seeker strategy. We believe that this is the first competency framework specifying conjointly individual and collective competencies as well as leadership competencies supporting a need-seeker innovation process.

After having observed that large French companies still do not manage their innovation process very well, we established the need for an organization and a methodology of radical innovation driven by uses. Since 2009, we have developed and tested a radical innovation methodology, called Radical Innovation Design® (RID), in order to meet the expectations of innovation management through uses. RID presents a structured process of problem posing and problem solving focused on obtaining pockets of value obtained by identifying important problems appearing in frequent use situations and for which existing solutions bring little or no improvement. These pockets of value are then strategically chosen by companies to establish a scope of ambition. The latter, which advantageously replaces the traditional marketing brief, is the starting point for highly effective targeted creativity sessions. The RID methodology is described through the example of a health innovation in the context of dental imaging.

The literature reports that abduction is inherent to design reasoning. The Radical Innovation Design methodology is analyzed using the lens of Kroll and Koskela's two-step innovative abduction. In the first phase (Problem Setting), the Knowledge Design process follows a two-step selective abduction and the Problem Design process comprises abduction followed by deduction. This illustrates the specific reasoning employed when identifying the right problem on which to innovate. In the second phase (Problem Solving), the reasoning follows two-step innovative abduction.

The Radical Innovation Design (RID) methodology has been developed for 10 years at CentraleSupélec. It is an integrated approach to radical innovation "driven" by unsatisfactory/problematic uses that differs significantly from traditional methods such as Design Thinking, CK theory, TRIZ, Business Model Canvas, Lean Startup, Blue Ocean Strategy. RID proposes a terminology, concepts, a process, algorithms and original tools that will be presented through industrial examples. A RID study starts from a field of activities (or uses) that must be systematically explored in order to properly define the problem. The convergence towards an innovative concept is done by systematic exploration of the problem and the opportunities.

Autonomous Vehicles (AV) are the future evolution of Land Transportation Systems (LTS). They promise an improvement in road safety. However, safety requirements stay a big challenge for their development. The literature presents a lack of insight on the way LTS safety requirements will evolve. This paper proposes an analysis method of LTS safety requirements evolution toward AV. The ASIL metric is used to evaluate the safety criticality. The application on two case studies, the steering by wire and platooning systems, results in a better understanding and characterization of this evolution.

The residential building is a major energy consumer and pollution source worldwide. The shift towards constructing energy-efficient buildings is impelling higher performance. In sustainable building, occupants become a major source of uncertainty in energy consumption. Yet, energy simulation tools often account for occupant behaviour through predefined fixed consumption profiles. Therefore, energy and buildings experts are in need for more precise methods for better forecasting the influence of occupants on the building performance. An activity-based framework for quantifying occupant-related energy consumption is proposed. The energy consumption is quantified per domestic activity as a function of households' socio-demographic and economic attributes. The aggregation of such domestic activity energy consumption provides an accurate estimation of the household energy consumption per daily, monthly and annually periods. First, a literature review about residential energy consumption and the existing modelling approaches is presented. Second, a systematic breakdown structure of energy end-uses is proposed. The activity-based framework is then introduced. An application example is demonstrated together with simulation results. Finally, model's utility is outlined and its possible implications are discussed.

With 270 million light vehicles and 20 million heavy-duty and off-road (HDOR) vehicles in use in the European Union, the automotive and HDOR industries form two major sectors of the European economy. Each year, 12 million light vehicles plus 1 million HDOR vehicles reach the end of their lives. In a circular economy perspective, the following two questions are of growing concern: (i) to what extent is the circular economy achieved and implemented in the automotive and HDOR sectors? (ii) what industrial practices and regulations are prevalent and commendable for the circular economy? The end-of-life management of light vehicles (subject to the ELV Directive 2000/53/EC) has been widely studied in the literature, but the end-of-life stage of HDOR vehicles has long been neglected by researchers. To fill this gap, both extensive literature survey and in-depth industrial investigations were conducted. Key factors, i.e. regulations, business models and market evolution, and integration of new emerging technologies affecting the circular economy performance of the automotive and HDOR sectors were analysed. Lessons learned from best industrial practices are highlighted, and remaining challenges for a more circular economy are identified. The two industries are compared in terms of the four buildings blocks of the circular economy and the four possible feedback loops defined by the Ellen MacArthur Foundation. This research contribution can lead on to practical applications, e.g. help industrial practitioners and policy makers take up the challenges and seize opportunities to close the loops for HDOR vehicles through different approaches.

Automobile ownership worldwide has exceeded 1 billion since 2010, and the U.S. plus the EU account for 50% of this total (Sakai et al. 2014). According to Wilson (2017), CEO of the U.S. Automotive Recyclers Association (ARA): “Different countries are on different parts of the path related to end-of-life management of vehicles. By looking at how other countries deal with their industry, one can choose some parts of the path that are desirable and try to avoid some of the paths that are unpleasant.” It is with this perspective that this communication initiates a discussion of the appropriate transfers and applications of recommended practices and know-how from one industrial sector (the automotive sector) to another (the heavy-duty and off-road (HDOR) sector) and from a geographic region (the EU) to another (the U.S.).

Designing a composite structure is a major challenge: while an engineer designing a mechanical product based on metallic material is mainly focused on developing a shape that will guarantee a specific behavior, the engineer for whom the design problem is that of a product based on composite materials must find the best shape - material structure combination. Thus, he must also simultaneously design a material and the product topology. The combinatorics are complex and the solution spaces are very large. CAD and finite element simulation tools do not provide the designer with an approach to explore the search spaces interactively and quickly. The thesis work leads to a new numerical approach to manipulate each design parameter characterizing a composite structure, regardless of the scale at which it is relevant.First, the Parametric and Reduced Behavior Model (PRBM) is a so-called separate model. It allows:1- a multi-scale approach: the mechanical parameters of the structure are explicitly described as coming from the material quality of each fiber, the matrix, each layer and the topology of the laminate itself,2- a multi-physics approach: independently the mechanical behavior of each layer and each interface is processed to give rise to the behavior of the laminate. Static and dynamic behavior situations are studied. In the case of dynamic behavior, the viscoelastic character became a conceptual issue.Secondly, a method mixing non-integer derivatives and use of the PGD method allowed the realization of the PRBM. Integrated in a Parametric Knowledge Model (PKM) with expert knowledge models, it is the basis of an interactive design support method.The PKM is processed by an evolutionary optimization method. The PKM is processed by an evolutionary optimization method. As a result, the designer can interactively explore the design spaces. To qualify our models and our PRBM, we study 2 design problems of laminated structures. The determined solutions are qualified against finite element simulations or according to an empirical approach.

There has been rising interest in confronting formal models of design with practical design methods, in order to understand better both and to explore how they can improve each other. In this article, we try to map the Radical Innovation Design (RID) methodology in Gero’s Function-Behavior-Structure (FBS) framework. We encounter difficulties in doing so, and propose new constructs extending the FBS framework to account for some processes in RID. For instance, FBS is extended to describe the early stages of RID, where usages are analyzed to identify the appropriate situations and problems on which to innovate. We present a short practical case study to illustrate the relevance of these concepts. Our findings join those of others who have investigated the use of FBS to illustrate innovative projects, where requirements are unclear. We propose perspectives for future research, notably pursuing this work with the situated FBS framework.

This thesis provides keys to measure, improve and pilot the circularity performance of industrial products at different scales of implementation of the circular economy (micro, meso, macro). Several circularity indicators are tested through an industrial case study and a critical analysis of these indicators is performed with respect to, among others, the circular economy paradigm, and their integration in industrial practices of (re)design and development of products and services. At the same time, in response to the growing number of circularity indicators developed, with unequal perimeters and ambitions, a taxonomy of circularity indicators is proposed in order to clarify the current vagueness around this nebula of circularity indicators. This ordered classification of indicators is accompanied by a computerized selection tool to facilitate their appropriate use. A new circularity indicator is also developed and tested, and recommendations for the development of future indicators are discussed. Although the indicators discussed in the thesis are intended to be used for any type of sector, the heavy vehicle industry is the framework for their application. Indeed, in the absence of European regulations on the end-of-life of these vehicles, the aim is to identify, question and test the action levers that this industry can activate to improve its performance in a circular economy perspective.First, the best practices and current challenges of the light and heavy vehicle industry are highlighted with respect to the four cornerstones of the circular economy defined by the Ellen MacArthur Foundation (circular design, new business models, reverse logistics, ecosystem) and the four main loops of the circular model (maintenance, reuse, reconditioning, recycling). These best practices are synthesized in a two-page guide to facilitate their dissemination and adoption by industrial practitioners wishing to implement such circularity models. Subsequently, a pilot industrial study was conducted with a material handling equipment manufacturer seeking to develop its end-of-life equipment reconditioning activity. Inspired by field investigations coupled with an extensive state of the art, a multi-scale modeling - a) machine and key components, b) dismantling process, c) recovery channels - allowed (i) to propose and validate an improvement (in time and resources) of the dismantling operations from an organizational and technical point of view, (ii) to carry out an economic and environmental analysis of the dismantling and recovery activities A first decision support tool has also been designed to assist the industrialist in the optimal recovery of his equipment at the end of its life. Reflections on the generalization and transposition of the developed approaches to other devices or sectors are given, as well as promising research tracks to further accomplish the transition towards a circular economy - effective, efficient and sustainable.

Automobile ownership worldwide has exceeded 1 billion since 2010, and the U.S. plus the EU account for 50% of this total (Sakai et al. 2014). According to Wilson (2017), CEO of the U.S. Automotive Recyclers Association (ARA): “Different countries are on different parts of the path related to end-of-life management of vehicles. By looking at how other countries deal with their industry, one can choose some parts of the path that are desirable and try to avoid some of the paths that are unpleasant.” It is with this perspective that this communication initiates a discussion of the appropriate transfers and applications of recommended practices and know-how from one industrial sector (the automotive sector) to another (the heavy-duty and off-road (HDOR) sector) and from a geographic region (the EU) to another (the U.S.).

Experimentation and validation tests, in the context of technology startups, are often costly, time-consuming, and, above all, not well organized. A review of the literature shows that existing tools and methods are either oriented towards lean iterative tests or strongly focused on technology improvement. There is therefore a gap to bridge by providing tangible decision-making supports involving both market and technology aspects. This paper introduces a new quantitative methodology called RITHM (Roadmapping Investments in TecHnology and Marketing), which is a structured process that enables startups to systematically experiment and reach, with relatively small effort, adequate maturity level for the most promising markets. The objective of this methodology is to model and optimize tests in the front end of innovation to progressively reduce uncertainties and risks before the launch of the product. A case study of a shape shifting technology is presented in this paper to illustrate the application of RITHM.

There has been rising interest in confronting formal models of design with practical design methods, in order to understand better both and to explore how they can improve each other. In this article, we try to map the Radical Innovation Design (RID) methodology in Gero’s Function-Behavior-Structure (FBS) framework. We encounter difficulties in doing so, and propose new constructs extending the FBS framework to account for some processes in RID. For instance, FBS is extended to describe the early stages of RID, where usages are analyzed to identify the appropriate situations and problems on which to innovate. We present a short practical case study to illustrate the relevance of these concepts. Our findings join those of others who have investigated the use of FBS to illustrate innovative projects, where requirements are unclear. We propose perspectives for future research, notably pursuing this work with the situated FBS framework.

Autonomous Vehicles (AV) are the future evolution of Land Transportation Systems (LTS). They promise an improvement in road safety. However, safety requirements stay a big challenge for their development. The literature presents a lack of insight on the way LTS safety requirements will evolve. This paper proposes an analysis method of LTS safety requirements evolution toward AV. The ASIL metric is used to evaluate the safety criticality. The application on two case studies, the steering by wire and platooning systems, results in a better understanding and characterization of this evolution.

No summary available.

No summary available.

Experimentation and validation tests, in the context of technology startups, are often costly, time-consuming, and, above all, not well organized. A review of the literature shows that existing tools and methods are either oriented towards lean iterative tests or strongly focused on technology improvement. There is therefore a gap to bridge by providing tangible decision-making supports involving both market and technology aspects. This paper introduces a new quantitative methodology called RITHM (Roadmapping Investments in TecHnology and Marketing), which is a structured process that enables startups to systematically experiment and reach, with relatively small effort, adequate maturity level for the most promising markets. The objective of this methodology is to model and optimize tests in the front end of innovation to progressively reduce uncertainties and risks before the launch of the product. A case study of a shape shifting technology is presented in this paper to illustrate the application of RITHM.

No summary available.

The issue of recovering platinum from catalytic converter of heavy vehicles, arises for economic (high valuable component due to the non-negligible presence of platinum that costs around 30 €/g), environmental (low platinum concentration in mines (below 10 g/t) requires large consumption of energy), social (ore mining conditions are increasingly drastic) and geostrategic (more than 90% of platinum stock is located in South Africa and Russia) reasons. Even if some marginal channels exist, the collection rate of platinum from catalytic converters in Europe is still low (around 50%) while recycling efficiency is high (around 95%). As heavy vehicles are not considered by any end-of-life directive contrary to the automotive sector submitted to ELV directive, the objective of this applied research work is to evaluate the impact of other actions levers to close the loop of heavy vehicles catalytic converters which contain larger amount of platinum than in cars. To date, a number of issues that still need to be tackling to close the loop of platinum have been outlined in literature but there is a lack of operational improvement proposal or simulation to see “what if” scenarios, and therefore evaluate the impact of different changes. Indeed, even though research the on end-of-life management has an extensive literature, there is still lack of in-depth investigation on how to effectively improve the overall end-of-life collection, recovery and efficiency related to platinum from heavy-duty vehicles catalytic converters. Thus, new insights are needed to address and overcome the barriers, systematically analysed in previous state-of-the-art, to an effective circular economy of platinum. In this light, the main objectives of this work are twofold, (i) to construct a methodology that aims at assessing the impact of different actions levers on the road toward the circular economy, (ii) to experience the proposed approach through a significant industrial case study from a manufacturer willing to know how close the loop of their product containing precious raw materials, in order to benefit from economic and environmental spinoffs. Through MFA and SD modeling and simulations, promising actions levers (e.g. re-design to facilitate end-of-life recovery, take-back and remanufacturing offers, product-as-a-service, mandatory recycling rate) will be analyzed. Also, methods of prospective will be used to define relevant and realistic scenarios. The developed approach will assess the contribution of different actions levers in “closing-the-loop” by simultaneously considering environmental and economic parameters. In this paper, we will try to summarize the issues of platinum recovery from end-of-life heavy vehicles, to explain in detail the approach and to present first results of application. The proposed method consists in five steps. First step is about modeling the current situation (defining scope, boundaries of the study, identifying stakeholders, representing value chain). Second step deals with the identification and selection of promising and possible action levers. Third step with scenarios elaborations. Fourth step with simulations realisation. Last step with results analysis and presentation to get feedback from actors. The broader impact of this work will be to provide significant new insights for industrial practitioners about mechanisms to maintain platinum deposit contained in catalytic converter in Europe and therefore to secure supply chain. As such, it will represent a valuable contribution to resource sustainability for European platinum sector in the light of the circular economy.

Integration, Verification and Validation (IVV) practices in simulation-based design helps reduce inconsistencies in multidisciplinary systems, i.e. those combining multiple mechanics, structural, hydrodynamic or other complex components. In current multidisciplinary simulation model development processes, subsystem simulation models are usually Verified and Validated (V&V) at supplier level to assess whether a system meets its intended goals. in such scenarios, each system is verified and validated separately – mechanical, structural, hydrodynamic, etc. However, many problems may arise during the actual integration of these modular subsystem simulations at the Original Equipment Manufacturer (OEM) level, which increases the risk of late inconsistencies such as interface mismatches or other interoperability-based problems. To address this problem, the present work aims to reduce late inconsistency detection through ensuring early stage collaborations between the different suppliers and the OEM by proposing a clear simulation model request. Our approach is illustrated with an industrial case study showing how a Model Request Package that contains the Model Identity Card (MIC) and Model of Intention (MoI) concepts, helps reduce the knowledge gap and inconsistencies between OEMs and model suppliers.

Affordance based design is developed since the beginning of 21 st century. Affordances being revealed properties of a system in a context, they may be much diverse and unexpected. Consequently, it is an utopia to think of enumerating all the existing precise affordances in advance. Presently, identifying affordances along a design or redesign process is based on experiments and focus groups, which are time and resource consuming. Although automatic identification strategies have been proposed, the lack of affordance database along with clear categorization technique makes it unpracticable and non-repeatable today. In this paper, the theoretical basis and technical basis of identifying affordances from online reviews are discussed. A framework of affordance identification is proposed by capturing constitutive affordance elements with natural language processing algorithms. Meanwhile, a case study of 303 review sentences of Kindle Paperwhite from Amazon.com is conducted with 1 expert in affordance based design and 6 participants. The result shows that the proposed framework is effective in affordance identification. It provides basis for automating the identification process in the future.

Urban mobility poses certain challenges to design practice. Mobility components such as vehicles, urban infrastructure, or services that are provided as part of a mobility experience are often designed separately. The overall performance of an urban mobility system, e.g. at the city level, is therefore broken down into several component performances. These are not integrated from the perspective of a user interacting with the whole, in a door-to-door mobility. This paper first links different perspectives of urban mobility by including, crescendo, the human in the production of a global design solution. Through a review of the design and transportation literature and practical examples, the paper highlights the complexity factors of urban mobility that change the boundaries of design engineering. The main contribution is to identify three types of relevant design objects, aiming to provide a language for designing urban mobility systems: mobility components, the traveler experience, and travel-oriented indicators.

In this article, a usage-driven perspective is taken to analyze the lack of industrial uptake of ecodesign tools in the construction sector. Eleven interviews with professionals were carried out to gain insight into the building design process, the roles of the different actors and their interactions. Nineteen further interviews investigated ecodesign knowledge and practice, and the barriers to wider implementation of this approach. The data drawn from the interviews were analyzed with the Dependency Structure Modelling Value Bucket (DSM VB) algorithm. The algorithm maps usage situations, designer issues and existing ecodesign tools to highlight gaps in the available offer for ecodesign tools. It appears that ecodesign tools are missing in the early design stages, and that what is most needed in these phases are tools for multicriteria analysis (economic, social, and environmental) and benchmarking. Tools answering these needs, combined with desirable changes we identified in the design process, would help ecodesign adoption.

Urban mobility poses some sustainability and design practice challenges. Mobility components such as vehicles, urban infrastructure, mobility services or other services delivered along a mobility experience are often designed separately. The performance of a global urban mobility system, at a city scale for instance, is therefore parceled out into components’ ones that are not integrated from the perspective of a user who interacts with them in a door-to-door journey. This paper starts with relating different perspectives of urban mobility including, in crescendo, the human in the production of a global design solution. Through the examination of design and transport literature as well as practical examples, the paper highlights complexity factors of urban mobility that challenges engineering design. A second contribution is to identify relevant design objects aiming at providing a language for designing urban mobility.

Companies make substantial R&D investments in early design stages to develop radically innovative products. However, despite abundant research work in the field of human-centered design, the front end of innovation is the least well-structured part of the innovation process. Radical Innovation Design (RID) methodology has put forward a structured process aiming at exploring, organizing and categorizing required knowledge to design a useful problem in the form of value buckets (i.e. overlooked problems of users) to be evaluated. In this paper, we aim at reinforcing the knowledge acquirement process in parallel with the problem design process to fine-tune the firm's R&D strategies, and to increase the likelihood of successfully reaching the mainstream markets. The contributions of this paper are twofold: i) to provide a set of knowledge acquisition rules in front end of innovation. and ii) to specify a set of problem design guidelines mainly by introducing a tool called Dependency Structure Modeling (DSM)-Value bucket algorithm, which enables a systematic identification of value creation opportunities. The example of a smart lighting project is analyzed in this paper as a case study.

Forming and sustaining an industrial symbiosis depends on several actors. Actors that have an interest in the symbiosis and the possibility to influence it are called " stakeholders ". According to social exchange theory and resource dependency theory, the power of actors in a network depends on the dependency of other actors on the resources they control. We adapt the stakeholder value network approach from the strategic management literature to the industrial symbiosis context as a means to provide insights into the power of stakeholders of an industrial symbiosis. The approach is applied to a waste incinerator steam network symbiosis case study in France, which has been successfully operated and extended over decades. The results from the case study show that using the stakeholder value network approach enables the assessment of the relative power of symbiosis stakeholders and to identify key resources on which their power is based. We propose the application of the approach to further case studies in order to identify patterns in the power distribution within symbiosis networks.

Industrial practitioners are increasingly willing to shift their products and businesses into more circular models. Circular economy paradigm requires optimization of system rather than components. Yet, existing methods and tools, intended to designers, engineers or managers, to assess and improve products' circularity potential are both lacking systemic vision and operational considerations. This research work contributes to fill this gap through the design of a holistic and integrated framework aiming at measuring, improving and monitoring product circularity performance. The developed framework is based on a hybrid top-down - objective-driven - and bottom-up - data-driven - approach including the four building blocks of the circular economy defined by the Ellen MacArthur Foundation. First mature steps of the proposed framework are detailed and experienced on an industrial case study. Insights for an enhanced products' circularity performance measurement and improvement framework are also discussed and lead to further promising research perspectives.

This research aims to study the environmental impacts of an emerging renewable-based electricity generation technology, geothermal stimulated systems (GS), through life cycle assessment (LCA).After analyzing several case studies, we developed a parameterized LCA model capable of characterizing the environmental performance of the GS system. Our results show that the life cycle greenhouse gas emissions of EGS are much lower than those of fossil fuel power plants.In a second step, we developed a methodological framework to apply global sensitivity analysis (GSA) to the LCA of emerging technologies such as EGS, taking into account the high uncertainties related to their innovative character. We have applied our new GSA approach to develop a simplified LCA model for decision makers, allowing a quick estimation of the impacts of EGS from only five key parameters: installed capacity, drilling depth, number of wells, geothermal flow rate and lifetime.The methodological approach developed in this thesis is applicable to other technologies and opens up broad research perspectives in the field of environmental assessment.

Assessing product circularity performance is not straightforward. Meanwhile, it gains increasingly importance for businesses and industrial practitioners who are willing to effectively take benefits from circular economy promises. Thus, providing methods and tools to evaluate then enhance product performance—in the light of circular economy—becomes a significant but still barely addressed topic. Following a joint agreement on the need to measure product circularity performance, this paper provides an overview of mechanisms aiming to help industrial practitioners in this task. In fact, three existing approaches to measure product circularity performance have been tested on an industrial case study and criticized regarding both their applicability in industry and their accordance with circular economy principles. Although these methods and tools deliver a first and rapid trend of product circularity performance, the whole complexity of circular economy paradigm is far from being considered. In addition, operational guidance for engineers, designers or managers to improve their products in a circular economy context are missing. As a result, both recommendations for industrial practitioners and guidelines for the design and development of new frameworks, tools and indicators aiming at measuring product circularity performance are provided. This includes cornerstones, key requirements and practical implications to support enhanced circularity measurement that will be developed in further work, accordingly to circular economy paradigm and industrial reality.

No summary available.

This paper proposes a template to assist food value chain actors in their collaborative efforts to develop common sustainable strategies and business models. Inspired by the simplicity of the Business Model Canvas, the template reintroduces sustainable practices as a support for management solutions for sustainable food value chains. The template requires cooperation between actors and stakeholders and comprises three steps: (1) identification of needs for sustainability. (2) development of value chain practices aimed to deliver sustainable value, and assignment of responsibilities to actors for these practices. and (3) formulation of a sustainable value proposition. The template also allows a simple graphical representation of sustainability in value chains, which helps improve communication between actors, and allows stakeholders to be kept informed. The template is applied to a sustainable pork value chain to illustrate how it captures various aspects of sustainability in the pork industry.

In this article we present the matchmaking problem in industrial symbiosis where wastes from one company is matched with resources of another company that could be substituted. Identifying potential matches is difficult, as it is based on process-specific knowledge that certain wastes can be used for specific processes. Capturing this knowledge in waste-resource matching rules manually is time-consuming. Therefore, we argue that a Natural Language Processing (NLP)-based approach of semi-automatically extracting rules from domain-specific data sets could be a viable approach to solving this problem. The basic NLP problem to solve is to find similar concepts (synonyms), part-whole relationships (meronyms), and " is a " relationships (hyponyms). Synonyms are important for finding wastes and resources that are named differently but refer to the object. Meronyms are part-whole relationships that may help to identify wastes with components that could be used as a resource. Hyponyms allow for building taxonomies. We present the results of an initial literature survey of algorithms that are able to find these relationships in large sets of unstructured text documents. Furthermore, we propose a research approach for further extending the literature survey and testing the existing algorithms on small test cases and realistic matchmaking case. For future work, additional problems that fall into the NLP category can be addressed such as semi-automatically identifying processes for converting wastes into resources.

A great deal of work has been done to characterize entire sets of ideation indicators as well as isolated factors of innovativeness. Nevertheless, entire sets of innovativeness indicators are essential in business innovation competitions, as well as within companies in order to select promising innovative project seeds. In this paper, a complete set of innovativeness indicators is proposed. The UNPC innovativeness model, standing for usefulness, newness, profitability and (proof of) concept, has been tested and validated over a period of 4 years within the largest European innovation cluster in the silver economy. Four authentic examples of innovation selections are analysed. They illustrate how the UNPC model is able to provide clear and efficient guidance for better decision-making in the context of innovating for the elderly. In addition, the UNPC primary diagnosis of an innovative project serves also as a map for continuous improvement or incubation of promising ideas or projects.

Whilst the diffusion and evaluation of healthcare innovations receive a lot of attention, the early design stages are less studied and potential innovators lack methods to identify where new innovations are necessary and to propose concepts relevant to users. To change this, we propose a structured methodology, Radical Innovation Design ® (RID), which supports designers who want to work on the unstated needs of potential end-users in order to create superior value. In this article, the first part of RID is introduced with its two sub-processes: Problem Design and Knowledge Design. In this first period, RID guides innovators to systematically explore users' problems and evaluate which ones are most pressing in terms of innovation, taking into account existing solutions. The result is an ambition perimeter, composed of a set of value buckets, i.e. important usage situations where major problems are experienced and the current solutions provide little or no relief. The methodology then moves on to Solution Design and Business Design (which are not detailed in this paper) to address the value buckets identified. With its emphasis on problem exploration, RID differs from methods based on early prototyping. The RID methodology has been validated in various industrial sectors, and is well-adapted for healthcare innovation. To exemplify the methodology, we present a case study in dental imagery performed by ten students in 8 weeks. This example demonstrates how RID favors efficiency in Problem Design and allows designers to explore unaddressed and sometimes undeclared user needs.

The experience that users have has recently become a major factor of differentiation between product and service companies (such as Toyota Motor Europe), leading to further research in the areas of user experience and interaction. These researches present a greater consideration of the subjective perception rather than the objective properties of the products.Starting from this approach of "design research" through the subjective perception, this study tries to understand and formalize the reciprocal influence between interaction and experience.From this approach of design research through subjective perception, this study tries to understand and formalize the reciprocal influence between interaction and user experience, defining which parameters affect subjective actions. From these parameters, this research has isolated the physical and digital properties of a product in order to highlight these effects on the affective and cognitive actions of the user.Thanks to this approach, this research leads to both scientific and industrial contributions: this research has made possible the formalization of the interdependence between the user experience and the interactions. the implementation of a taxonomy of interactive products through the meta-thorical approach of physical and digital interaction. and the materialization of a methodology and tools to both evaluate and create interactions from the experimental approach.

Design space exploration refers to the systematic activity of discovery and evaluation of the elements in the design space in order to identify optimal solution by reducing the design space toward an area of performance. Designers sample thousand design points iteratively, explore the design space, gain knowledge about the problem and make design decision. According to the literature, Design Space Exploration results in a decision of quality called informed decision which is supported by information visualization. Indeed, the representation of design points is seen as primordial to gain understanding of the problem and make an informed decision. Thereby, in our work, we try to identify which graph is the most suited to the discovery phase and allows designers to make an informed decision. We designed a web platform with four design problem and carried out an experiment with 42 participants. It results one graph more suited to make a decision of quality and to gain the most understanding: the Scatter Plot Matrix.

Today, the environmental problems become serious and they are highlighted in regulations frameworks. Then, the use of Life cycle assessment (LCA) tools, for assessing products environmental impacts, is necessary, till Computer Aided Design (CAD) phase, for manufactures aiming at guarding their market places. Required LCA data (processes) can be provided from CAD and Product Life Management integrated systems (CAD/PLM), which became a necessity for industries to manage easily their data. In this paper, we propose a new CAD data model oriented ecodesign which we name " Eco-feature " , based on the exploration of CAD/LCA systems to extract possible features life cycle scenarios, in order to select the most ecological one. Hence, firstly, we present the state of the art of researches aiming at connecting CAD/PLM systems to LCA tools. Secondly we present our new approach and describe its advantages. Finally, we present a case study to valid the new proposed concept.

Most of methodologies, concepts and tools, which integrate Computer Aided Design (CAD) and Life Cycle Assessment (LCA) systems and aim at ecodesigning, are generally oriented to the environmental assessment. The environmental improvement is treated only in a few works. however it is a pivotal phase in the eco-design process. In this paper, we propose a new environmental improvement process based on the remaining Degrees of Freedom (DoFs) for CAD designer on which he can act to eco-design his/her CAD model. The originality in this process is the expression of a CAD model environmental impacts in function of CAD designer DoFs, aiming at help non environment experiment designer to eco-design products in CAD phase. For this, first, we present the concept of DoFs and we use it to identify the CAD designer action zone. Second, we establish the impact matrix of DoFs in each life phase, then. we develop the global impact matrix .The assembly of EIs by linear summation of the matrix columns shows the most impacting ones. Finally, we consider a case study to valid our proposed approach and results are shown in function of DoFs.

Privacy by design places the user's privacy and the protection of his/her personal data as a basic principle in the early stages of the design and decision-making process. In 2018, Privacy by Design will become a mandatory provision for any entity across the world which collects and processes European residents' personal data. In other words, more than a methodology, Privacy by Design is soon to become a legal requirement, the infringement of which may be subject to fines up to 2% of a company's total worldwide annual turnover. However, we argue in this article that Privacy by design is not merely a legal requirement that solution designers and providers need to comply with, but that the lack of respect for users' privacy is increasingly becoming a pain for users, with the aid of the pain-driven Radical Innovation Design (RID) methodology. Thus, we will show that Privacy by design may increase the value creation of a solution and that integrating privacy as a default setting in the design of a solution is becoming an essential factor for success on the market. This paper is a proposal and first attempt to evolve from Privacy by Design to a Design for Privacy.

This research work proposes a methodological approach to characterize and anticipate the organizational disruptions induced by a major information system innovation. The context considered is that of B2B, consisting of a solution provider and a user-client of these solutions. It is therefore interested in products whose implementation leads jointly to a creation of value for the customer and a modification of the professional interrelations between the client company's businesses. Industry 4.0 is the context of experimentation for this paper. The challenge is to design products or services that take into account organizational changes in order to maximize their value and promote their adoption. The contributions of this research are positioned at two levels. On the one hand, a methodological approach is proposed. It allows for a better description of the opportunities for value creation induced by a better definition of the structures and expectations of the actors in the client organizations. On the other hand, a capitalization of the data collected from clients is proposed. The latter are based on a revisited use of the concepts of "customer concerns" and "personas". The contributions were elaborated from a case study: the upstream phase of a design process deployed in an industrial automation supplier.

In this article we present the matchmaking problem in industrial symbiosis where wastes from one company is matched with resources of another company that could be substituted. Identifying potential matches is difficult, as it is based on process-specific knowledge that certain wastes can be used for specific processes. Capturing this knowledge in waste-resource matching rules manually is time-consuming. Therefore, we argue that a Natural Language Processing (NLP)-based approach of semi-automatically extracting rules from domain-specific data sets could be a viable approach to solving this problem. The basic NLP problem to solve is to find similar concepts (synonyms), part-whole relationships (meronyms), and " is a " relationships (hyponyms). Synonyms are important for finding wastes and resources that are named differently but refer to the object. Meronyms are part-whole relationships that may help to identify wastes with components that could be used as a resource. Hyponyms allow for building taxonomies. We present the results of an initial literature survey of algorithms that are able to find these relationships in large sets of unstructured text documents. Furthermore, we propose a research approach for further extending the literature survey and testing the existing algorithms on small test cases and realistic matchmaking case. For future work, additional problems that fall into the NLP category can be addressed such as semi-automatically identifying processes for converting wastes into resources.

Operational Technologies (OT) are designed to monitor and control plants. OT are increasingly mixed with Information Technologies (IT) in global solutions. A conventional customer inquiry is no more sufficient to get enough data about Customer Concerns (CC). Indeed, an IT OT solution is the nervous system of a company. it intertwines people processes and functions. For specification step, one must now capture negative perceptions in the interrelationships with other actors of the customer company. The paper creates a database of CC describing dissatisfactions between several involved personas.

All women have to deal with menstrual cycles.The paper proposes to investigate usage and sustainability performances of four hygienic solutions, i.e. environmental, economic, hygienic, comfort and social performances. Three different geographical contexts are also studied: Europe, United States and India, where product expectations, cultural aspects, production and logistic realities strongly differ and influence the purchasing choice. Products sustainable performances are fanally combined with client's preferences to identify the product that fit the best the clients' expectations.

In industry circles, customer " pain points " has replaced customer needs as the source of ideas for products and services. The premise is that the more pressing the 'pain', the more likely the customer will seek to find a solution. In this article, we develop a model to describe customer pain induced by a product. The model includes semantics to describe the pain elements and relations between the semantics. We evaluate the model to ascertain the extent to which individuals can use it consistently to identify pain points in a dataset of consumer product injuries. The paper concludes with a discussion on the use of the model in a pain-minimization design process, in which the aim is to bring essential health, social, and economic value.

The building stock accounts for between 16 and 50 percent of national energy consumption worldwide [1–3]. Governments around the world are thus rolling out energy directives, national regulations and energy-efficiency labels that set minimum requirements for buildings' performance [4], and promote the construction of green buildings [5]. Buildings' stakeholders have thereby started dealing with buildings as products-with-services rather than just simple products. Services may for instance include energy monitoring or equipments' maintenance during a building's use-phase. Moreover, new market expectations such as the 'energy performance contracts' have started to emerge in a number of countries [6]. Such services and offers require thus a better control of performance's variability during a building's lifecycle. Consequently, a better comprehension and consideration of the key determinants of energy performance has become essential for the design and marketing processes of buildings. Occupant behavior is a substantial source of uncertainty in energy modeling since. It can impact energy consumption by as much as 100% for a given dwelling [2,7–14]. Industrial energy simulation tools such as Energy Plus and eQUEST propose some simplifications regarding occupants' behavior (among other simplifications), which may lead to unrealistic energy estimates, and may eventually be one of the reasons behind high discrepancies between predicted and real energy consumption values [15–18]. Nowadays, such performance discrepancies are no longer tolerated-especially in the case of green (energy-efficient) buildings. More precise methods are therefore needed to model occupants' influence on buildings' energy performance. Such models should result in more accurate energy estimations, and hence improve building designs and marketing offers. The authors have proposed an activity-based model of residential energy demand (SABEC, standing for Stochastic Activity Based Energy Consumption) in a doctoral dissertation [19]. The present paper is not intended to detail the model, but it briefly recalls the adopted modeling methodology. The main focus here is to show how a user-focused model, which accounts for occupants' energy-related needs and activities, can be used within the engineering design, energy management processes, and marketing offers of residential buildings. 2 Book's title A literature review is first presented followed by a brief recall of the proposed modeling methodology and a sample of simulation results. The possible integration of the proposed model into the design and energy management processes of residential buildings is then demonstrated through a number of use cases.

In this paper, the importance of problem setting in front end of innovation to radically innovate is emphasized prior to the use of the BMC. After discussing the context of the Business Model Canvas usage, the failure reasons of a premature use (in early design stages) of the BMC tool is discussed through some real examples of innovative startups in Paris area. This paper ends with the proposition of three main rules to follow when one wants to use the Business Model Canvas.

Ambitious building retrofits are often hardly justified by energy savings only. A previous research project has shown that dividing by two the energy consumption of a building (like a school) may lead to a return on investment superior to 25 years [RS4E, 2010]. In this configuration, decision-makers are often not inclined to invest. Thus there is a need to investigate in more details and highlight the benefits of such retrofits or new buildings with a broader point of view. That is why the DECADIESE methodology has been developed by a consortium of major construction and energy companies (EDF R&D, Bouygues Construction, Vinci Construction, Foncière des Régions) and academic partners (CentraleSupélec, Université Paris Diderot – Paris VII, Mines ParisTech) in the frame of a French research agency-supported research project (2012-2014). DECADIESE considers an extended value of a building by incorporating sustainable dimensions through externalities integration, but also by recentering the value created by a building around the benefits for its users. This paper focuses on the latter. On one hand, costs are broken down into seven usage functions, which highlights possible mismatches between functional objectives and associated amounts of money. On the other hand, the functional performance of the building is assessed thanks to 95 criteria that are then aggregated into seven usage functions scores. Once those elements identified, DECADIESE gives to a project owner the ability to compare building variants. A complete overview of the methodology is given in section 2, and the functional aspects are explained in more details. Section 3 presents the first results and a short discussion. Finally, section 4 highlights the main conclusions and perspectives.

This paper aims at investigating, through several examples of innovative startups, different categories of Urban-Centered Innovative (UrCI) design solutions as well as the necessity to conduct real life experimentations supported by public and private stakeholders. This research will also shed light on the reasons why some urban-centered innovations are not efficient, and provides as well decision-making elements intended for startups and public administrations in order to improve the efficiency of UrCIs.

In Design by Shopping, designers explore the design space to gain an insight into trades, and feasible and impractical solutions, as well as to learn about alternatives before optimization and selection. The design space consists of multidimensional sets of data and, in order to select the best design from among numerous alternatives, designers may use several different graphs. In this study, we test to find the most appropriate graph to indicate the best solution corresponding to a set of objectives represented by a design scenario (1). A further constraint is that this must be done in the shortest possible time (2). Three graph types are tested in three different design scenarios where one car has to be chosen from a total of 40. A response quality index is proposed which computes the quality of a designer’s choice for any given scenario. In total, 90 tests with 30 participants were performed. The parallel coordinates plot proved to be the best graph for selection in Design by Shopping.

Academics-Industrial Sustainable Development Meeting - Edition 2016: ELV, what is the responsibilities of actors? This workshop is hopefully the beginning of a series of annual meetings between academics and industrial managers on the subject of sustainable development. Recycling end-of-life vehicles (ELVs) and the responsibilities of the actors involved will be the focus of our first workshop JUIN-DD’16. End-of-life vehicles are considered hazardous waste that should require special treatment in order to avoid environmental and social risks. The EU Directive on ELV, which was introduced on January 1, 2015, requires that the reuse and recycling be increased to a minimum of 85% by an average weight per vehicle and year. Yet, heavy-duty vehicles and non-road mobile machinery are not covered by such regulations. Meanwhile, automotive manufacturers have implemented various activities and processes to comply with this regulation including eco-design, recycling, remanufacturing, reconfiguring, disassembling, research and development, etc.

Industrial symbiosis can be understood as the substitution of new resources used in an industrial process by another resource that would otherwise be discarded. Industrial symbiosis can thereby create new revenue streams and at the same time reduce environmental impact. The initial step in creating an industrial symbiosis is the identification of potential substation relationships between production plants. This step is challenging, as information about the companies is often not available. Several software tools have been developed in order to identify potential symbiosis opportunities. However, these tools have the shortcoming that they require extensive data input from companies owning the production plants. This requirement limits the number of companies for which symbiosis opportunities are identified. In this paper, we propose a data-driven methodology for identifying industrial symbiosis and generating eco-industrial park architectures. The methodology is based on meta-models of industrial plants for identifying plant attributes for certain types of plants, correlations that estimate the rough amount of resource supply and demand of a plant, and a rule-based system that identifies symbiosis opportunities based on knowledge from successful symbioses. Based on the symbiosis opportunities, approach generates eco-industrial park architectures that are optimal in terms of economic and environmental performance. Finally, we apply the methodology to a case study of the existing Kalundborg eco-industrial park to evaluate if the methodology is capable of finding existing symbioses. We conclude that the methodology can be applied to screening industrial zones with standard types of industrial plants. However, the results depend on the types of existing industrial plant meta-models in the database. Future work will focus on extending the data and knowledge base. and validating the methodology by its application to other existing eco-industrial parks.

The Dependency Structure Modelling Value Bucket (DSM-VB) tool is integrated into Radical Innovation Design (RID) methodology in order to explore the front end of innovation in need seeker mode. The determination of innovation opportunities, here called value buckets, has been automated by matrix representations of dependencies between problems or pain points, usage situations and existing solutions. Three matrices are built along the problem setting stage of a RID process. The first matrix expresses which problems occur during usage scenarios, the second how far existing solutions cover problems, and the third to what degree existing solutions are useful in usage situations. Combining these three matrices results in a matrix of value buckets, which represents the combinations of important problems which occur during characteristic usage situations and for which few existing solutions are useful or efficient. This outcome allows focused creativity workshops to be run, resulting in usage innovations with a high likelihood of market success.

Industrial symbiosis can be understood as the substitution of new resources used in an industrial process by another resource that would otherwise be discarded. Industrial symbiosis can thereby create new revenue streams and at the same time reduce environmental impact. The initial step in creating an industrial symbiosis is the identification of potential substation relationships between production plants. This step is challenging, as information about the companies is often not available. Several software tools have been developed in order to identify potential symbiosis opportunities. However, these tools have the shortcoming that they require extensive data input from companies owning the production plants. This requirement limits the number of companies for which symbiosis opportunities are identified. In this paper, we propose a data-driven methodology for identifying industrial symbiosis and generating eco-industrial park architectures. The methodology is based on meta-models of industrial plants for identifying plant attributes for certain types of plants, correlations that estimate the rough amount of resource supply and demand of a plant, and a rule-based system that identifies symbiosis opportunities based on knowledge from successful symbioses. Based on the symbiosis opportunities, approach generates eco-industrial park architectures that are optimal in terms of economic and environmental performance. Finally, we apply the methodology to a case study of the existing Kalundborg eco-industrial park to evaluate if the methodology is capable of finding existing symbioses. We conclude that the methodology can be applied to screening industrial zones with standard types of industrial plants. However, the results depend on the types of existing industrial plant meta-models in the database. Future work will focus on extending the data and knowledge base. and validating the methodology by its application to other existing eco-industrial parks.

Eco-design becomes more and more recognized and well deployed in competitive mass-consumer goods producers (B-to-C). However the situation is not so advanced in B-to-B industries, in particular for complex industrial systems, characterized by a very long and uncertain life cycle, a high number of subsystems and components or strong interactions with their environment. The technological and regulatory constraints associated with these systems may slow down the ability to innovate, as reliable and long-term proven technologies are often favored. Nevertheless the need for eco-innovation is clearly present, however to eco-innovate on complex industrial systems is a hard task. R&D projects in complex systems industries are often driven by technological and not environmental considerations. These project need to be identified really early in the design process, with few information. On the other hand everybody agrees that environmental-oriented R&D projects are necessary, but the product complexity makes the initiation of an eco-innovation approach tricky, and only few R&D decision-makers are trained in eco-design or eco-innovation. That is why a simple and effective eco-innovation method is necessary, with little necessary preliminary environmental knowledge and stimulating the collaboration. Thus we propose in this paper such an intuitive eco-innovation process. It permits to identify at a strategic level and with limited time and resources eco-innovative R&D projects through a multidisciplinary working group.

Based on extensive industrial investigations (regarding HDOR Vehicles features, regulations, sustainable issues, and emerging technologies) and on scientific gaps identified through literature review, the following research question emerged: “How to optimize the sustainable management of a fleet of HDOR throughout all life cycle, at different scales and for all stakeholders thanks to the help of the IoT & Telematics?” The purpose of the research work is then to develop relevant industrial design frameworks and methods to support industrial and policy strategic decisions concerning the life cycle of heavy vehicles at different scales (i.e. currently on construction (Design). on the market (Use).

Eco-innovation methodologies and tools are being applied in companies to an increasing extent. None of them, however, are particularly adapted to complex systems industries, where the eco-design requirements are highly specific. These systems are characterized by large size and mass, and relatively long and uncertain life cycles. The associated organization is also complex as there are multiple highly specialized experts, who rarely collaborate, and much less so on environmental aspects. In this paper, an adapted eco-innovation process based on the eco-design strategy wheel is proposed for use with a working group of internal technical experts. A first phase involves generating a high number of potential eco-innovative R&D projects that are then analyzed and assessed using an appropriate multi-criteria grid. Three structured filters enable an informed selection of the most promising projects that will then make up a balanced R&D project portfolio. The whole process has been successfully applied at Alstom Grid on large electrical stations used in the primary aluminium industry.

All women have to deal with menstrual cycles.The paper proposes to investigate usage and sustainability performances of four hygienic solutions, i.e. environmental, economic, hygienic, comfort and social performances. Three different geographical contexts are also studied: Europe, United States and India, where product expectations, cultural aspects, production and logistic realities strongly differ and influence the purchasing choice. Products sustainable performances are fanally combined with client's preferences to identify the product that fit the best the clients' expectations.

A great deal of work has been done to characterize entire sets of ideation indicators as well as isolated factors of innovativeness. Nevertheless, entire sets of innovativeness indicators are essential in business innovation competitions, as well as within companies in order to select promising innovation seeds. In this paper, a complete set of innovativeness indicators in the context of innovating in healthcare is proposed. The UNPC innovativeness model, standing for usefulness, newness, profitability and (proof of) concept, has been tested and validated over a period of 4 years within the largest European innovation cluster in the silver economy. Four authentic examples of innovation selections are analysed. They illustrate how the UNPC model is able to provide clear and efficient guidance for better decision-making in the context of innovating for the elderly. In addition, a framework for monitoring an innovative idea or project, and for increasing its maturity, is proposed. The UNPC monitoring process starts with the SWOT analysis of competing ideas. It then becomes dynamic, looking for new evidence for increasing the certainty and impact of UNPC proofs of the competing ideas. The model has been successfully used for upgrading a popular smart application on activity tracking.

Cities play an essential role in facilitating and supporting the real-world experimentations (for instance in public spaces with real users) of innovative products and services in the field of clean technologies. In this respect, the City of Paris has implemented an experimentation mechanism to help innovative start-ups improving their solutions and robustifying their business models in a multi-stakeholder ecosystem. Nonetheless, a primary investigation demonstrated that the efficiency of these in vivo in situ experimentations have means of being improved. To deal with this issue, the current paper proposes a critical review and a characterization of the existing projects related to clean technology and sustainability themes. A study over 25 experimentation projects results in identifying matches and mismatches between the expectations and the obtained results of tests by innovative start-ups. We have statistically demonstrated that the most important purpose of running experimentation projects by start-ups is to test and build a relevant " stakeholders network " around their businesses. Furthermore, we have assessed the influence of these experimentations on the design of innovative products.

A lot of work is done on ideation metrics but less is done for innovation metrics, i.e. monitoring an ideation process with the goal of augmenting idea maturity and increasing likelihood for the idea to be transformed into an innovation success on the market. To that aim, metrics of utility, profitability and proof of concept (feasibility) are considered along with innovation (novelty). This set of four metrics is used to dynamically investigate the probability of ideas to get high impacts on Utility, Innovation, Profitability and Concept (UIPC). The collection of new arguments is driven by the search of a sufficient certainty to get a satisfactory UIPC impact. Idea maturation process may be justified and traced, and idea selection facilitated and accelerated. This process is applied for developing an innovative smartphone application that can monitor health parameters.

This chapter synthetizes the round table chaired during the last part of the workshop by Pr. Bernard YANNOU with six industrial and institutional participants, whose short biography is provided below. The objective of the round table was to confront the research work presented in the previous parts of the workshop with the reality of companies and territories. Several questions were answered by the participants during one hour. The main messages are synthetized in the next sections. First each participant was asked to present one typical example related to eco-innovation in his/her organization. Then the second part of the roundtable consisted in questions from the audience and from the chairman, before concluding on some key take away messages to academic researchers.

Ambitious building retrofits to improve energy performance are often hardly justified by energy savings only. Indeed the return on investment to divide energy consumption of a building by two is more than 25 years, which often discourage investors. Energy efficiency thus needs to be considered differently to be economically justified. That is why a new methodology called DECADIESE has been developed by a consortium of major companies from the French building sector and academic partners. Broader than an energy efficiency focus only, DECADIESE aims at capturing the sustainable value of a building with an original focus beyond the scope of classical analytic methods, by extending the perimeter of associated stakeholders in order to allow ambitious building projects. DECADIESE considers an extended value of a building by incorporating economic, social and environmental aspects through externalities elicitation and integration with a multi-stakeholders point of view, but also by recentering the value created by a building around the benefits brought to its users through a functional approach. The methodology is built around a structured process involving multiple stakeholders (such as building owner, building owner assistant, engineering contractor, potential users and neighbours…) that contribute to feed the different modules of an experimental tool, finally aggregated in cost-benefits indicators. This paper focuses on the functional part of this model. On the one hand, buildings costs are first broken down into usage functions following a process inspired from value engineering standards. Usage functions costs offer a new vision of costs breakdown for a building, which highlights possible mismatches between functional objectives for users and associated amounts of money. On the other hand, the functional performance of the building is assessed thanks to a grid composed of 95 qualitative and quantitative criteria. Those elementary scores are then aggregated in 7 usage functions scores thanks to a fuzzy logic model based on building experts rules. Once those elements identified, DECADIESE proposes to a project owner a new vision of its project and the ability to compare building variants. DECADIESE has been experimentally applied on several case studies. Results show a good relevance of results and reveal a high interest of building sector actors. Next steps are underway to make the methodology more reliable and usable by building sector actors.

The use of numerical techniques during the design of a product has become widespread over the last 30 years. However, the slowness of the calculations and the specialization of the numerical models remain problematic. We have therefore chosen to develop reduced models of the scavenging behavior of a 2-stroke diesel engine with lights. These models are analytical, generic, fast to use and allow to eliminate the problems of numerical processing. They are also powerful tools in the search for design solutions. A 2D CFD model was first developed to serve as a database, with the definition of the most important parameters to follow in order to quantify an optimal sweep.The research work unveiled a novel methodology based on a meta-model of the so-called "neuro-separated" behavior including a neural state model, a pseudo-dynamic neural model and a separate variable model. Then, a decision support process exploiting the previous models was implemented through an evolutionary optimization process (based on genetic algorithms) and the rapid behavioral simulation of optimal design solutions by kriging.The multi-point of view, multi-criteria and multi-physics design approach applied to the engine also integrates a cognitive dimension: the evolutionary exploration of the solution spaces was conducted in a free and forced way. In order to validate our approach, we have set up qualification criteria applied to each of our models, allowing to quantify the deviations from the initial CFD base which founded our reduced models.our approach has led to the creation of a modeling and decision support tool using the Python and Matlab modules developed.

Social media gives new opportunities in customer survey and market survey for design inspiration with comments posted online by users spontaneously, in an oral-near language, and almost free of biases. This new source however has huge size and complexity of data needed to be processed. In this paper, we propose an automated way for processing these comments, using sentiment rating algorithm. Traps like negations, irony, smileys are considered in our algorithm. We validate it on the example of a commercial home theatre system, comparing our automated sentiment predictions with the one of a group of 15 test subjects, resulting in a satisfactory correlation.

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In design space exploration, the data resulting from the simulation of a large number of design alternatives can lead to information overload when it comes to choosing a good design solution. This design space exploration is similar to a multi-criteria design optimization method but in a manual mode for which appropriate multi-dimensional data visualization tools are employed. For the designer, a three-phase process - discovery, optimization, selection - is followed in a Design by Shopping paradigm. By "shopping" the design space, intuition about feasible and infeasible solution subspaces and solutions with good tradeoffs is gained. The designer learns during these graphical data manipulations. The selection of an optimal solution is thus based on an informed decision. The objective of this research is the performance of graphical representations for design space exploration, for the three phases of the Design by Shopping process. For this purpose, five graphical representations, identified as potentially performing, are tested through two experiments. In the first one, thirty participants tested three graphs, for the selection phase in a multi-attribute situation, through three design scenarios where a car has to be chosen among forty according to stated preferences. For this, a quality index is proposed to calculate the quality of the designer's solution for one of the three defined scenarios, the optimal solution according to this index being compared to those obtained after manipulation of the graphs. In the second experiment, forty-two novice designers solved two design problems using three graphs. In this case, the performance of the graphs is tested for informed decision making and for the three phases of the process in a multi-objective situation. The results reveal that one graph is suitable for each of the three phases of Design by Shopping:: the Scatter Plot Matrix graph for the discovery phase and for informed decision making, the Simple Scatter graph for the optimization phase and the Parallel Coordinate Plot graph for the selection phase in both a multi-attribute and multi-objective situation.

Design space exploration, that is an embodiment of a paradigm Design by Shopping, refers to the systematic activity of discovery and evaluation of the elements in the design space in order to identify optimal solution by reducing the design space toward an area of performance. This activity is composed of three main phases: the discovery, the optimization and the selection. There are existing tools for the design space exploration with different graphs (ScatterPlot matrix, 2D and 3D scatter plot, parallel coordinates plot, etc.). These graphs are useful for the representation of multidimensional set of data with an unlimited number of alternatives (design points). Obviously, during the selection phase, designers face to a reduced design space with a limited number of design points (in a performance area). Thus, in our work, we try to identify which graph is the most adapted to the selection phase. It emerges, from literature, three graphs useful for the representation of multidimensional set of data (>3 variables) and with a limited number of alternatives (<50). Thus we have designed experimentation composed of 3 scenarios (with 13 design parameters and 5 variables of performance) performed by 30 participants. It results one graph more suited to the selection phase in the Design by Shopping: the Parallel Coordinates Plot.

Today , industry is under constant pressure to increase competitiveness and resource-efficiency. One possibility to cope with these challenges is industrial symbiosis. Industrial symbiosis is based on substituting a new resource by an undervalued resource such as waste. Thereby , industrial symbiosis reduces waste and saves resources. One of the practical challenges in developing industrial symbioses is the identification of symbiosis opportunities. In particular , the question how " new resource – substitute " combinations can be identified has not yet been addressed in the literature. This paper presents a modeling approach for industrial symbioses in industrial parks , based on design structure matrices (DSM) , which intends to support the identification of substitution opportunities. The approach is applied to a sample industrial park. Combined with an optimization algorithm , the symbiosis model is used for identifying not only symbiosis opportunities but also the most attractive combination (s) of symbioses within the industrial park .

Environmentally conscious manufacturing process (ECMP) has become an obligation to the environment and to the society itself, enforced primarily by governmental regulations and customer perspective on environmental issues. ECMP involves integrating environmental thinking into new product development. This is especially true in the computer-aided design (CAD) phase which is the last phase in the design process. At this stage, more than 80 % of choices are done. Feature technology (FT), the core of the CAD phase, is then used to integrate environmental aspects. Also, integrations realized on CAD systems, such as computer-aided manufacturing (CAM), computer-aided process plan (CAPP), and product life management (PLM), are explored to eco-design products. This paper presents a new methodology for the selection of a green manufacturing process based on CAD features and CAD/CAM/CAPP/PLM in-tegrations. Firstly, we present an overview of works using FT in the CAD phase to reduce the environmental impacts of a manufacturing process. Secondly, we propose an approach based on FT for selecting an ECMP to promote a new simple eco-design tool which helps inexperienced eco-designers. Finally, a case study is considered to validate the proposed approach and results are commented.

Cities play an essential role in facilitating and supporting the real-world experimentations (for instance in public spaces with real users) of innovative products and services in the field of clean technologies. In this respect, the City of Paris has implemented an experimentation mechanism to help innovative start-ups improving their solutions and robustifying their business models in a multi-stakeholder ecosystem. Nonetheless, a primary investigation demonstrated that the efficiency of these in vivo in situ experimentations have means of being improved. To deal with this issue, the current paper proposes a critical review and a characterization of the existing projects related to clean technology and sustainability themes. A study over 25 experimentation projects results in identifying matches and mismatches between the expectations and the obtained results of tests by innovative start-ups. We have statistically demonstrated that the most important purpose of running experimentation projects by start-ups is to test and build a relevant " stakeholders network " around their businesses. Furthermore, we have assessed the influence of these experimentations on the design of innovative products.

You want to initiate an innovation project. You have an initial idea. However, it is necessary to be structured and to increase your skills and knowledge (we are talking about investigation here), i.e. to take the time to pose the problem rather than to rush headlong into the development of an imperfect solution. This sheet will help you initiate an innovation project in an organized way, by planning the investigation tasks that will allow the project team to increase its skills and knowledge through "knowledge books". The investigation logbook aims at creating a common framework for the project team members to distribute work packages and responsibilities on key themes identified in a collegial way. The investigation logbook is the first deliverable of the Radical Innovation Design® (RID) methodology, described in detail in various practical sheets. It really allows to launch a RID innovation project. It is strongly linked to the second deliverable of the methodology (cf. Énoncé un besoin idéal - Ref. Internet : 0424 and RID : Observation des usages - Ref. Internet : 1448), the re-problematization (the two deliverables are self-sustaining), and allows directly to initiate the third deliverable, the observation of the uses.

An eco-industrial park is a set of businesses that share resources in order to increase profitability and reduce environmental impact. The implementation of eco-industrial parks may significantly contribute to the creation of a sustainable economy. Despite this prospect , the actual development of eco-industrial parks is challenging , as a variety of factors must be considered. Not only technical , economic , and environmental factors are relevant but numerous stakeholder relationships as well , such as between firms , governmental bodies , and local communities. This paper presents a conceptual framework that is used to capture these diverse aspects and the relationships between them. The Unified Modeling Language (UML) is used for modeling its concepts and relationships. First , based on a literature survey , relevant concepts of eco-industrial parks are identified. One central concept is " industrial symbiosis ". A novel value-based interpretation of industrial symbiosis is presented. Second , the park ' s economic , local and regional development context , as well as its internal technical components and their relationships are modeled. Finally , the framework is used for modeling a concrete eco-industrial park , in this case part of the Kalundborg eco-industrial park .

In an eco-innovation approach, companies seek to invent and implement new, more sustainable activities that sometimes break with their existing practices, and that lead to more or less significant changes in their offers, their business model, and sometimes in their entire ecosystem. Faced with such challenges and associated dynamics that are often complex in nature, whether technical, economic, social, legal, political, etc., the company and the stakeholders of the emerging project do not always seem to be able to consciously move away from existing cognitive frameworks to explore alternatives that are in line with the initial ambitions of an eco-innovation project. The work presented here focuses on the maturation phase of eco-innovation concepts and seeks to develop support methods to avoid or overcome such situations, known as "collective fixation".The methodological approach is based on a research-action carried out within the support organization Apesa and structured in two steps:- The analysis of three cases of eco-innovation projects allowed us to characterize the problematic of support practices and more precisely the collective fixations present during the maturation of concepts. The MIRAS method proposes a panel of animation tools intended for the actors of the accompaniment to help the project groups during the phases of maturation of their concept and their potential of sustainability by aiming at a certain balance of the economic - environmental - social triptych.) In this perspective, MIRAS aims to adopt a systemic thinking, which is not only centered on the company but which reconsiders all the dimensions of the "extended network of stakeholders".

For a designed part, if different sets of features are used for machining, the manufacturing Environmental impacts (EIs) as well as cost may vary. In this research, a new methodology based on feature technology is proposed in order to help designer till detail design phase to choose the most optimal compromise Environmental Impact/Cost in manufacturing process. Hence an Environmental impact/Cost model is presented. This model follows the activities required for machining a set of features which are tool setups , fixturing setups and machining tool paths. The paper starts by presenting features based models which are the base of the methodology proposed. Then, a state of the art about using Feature technology in reducing on one side manufacturing cost and on the other side manufacturing environmental impacts is presented. Finally an environmental im-pact/cost methodology for evaluating multiple feature-base machining methods is proposed.

Social media give new opportunities in customer survey and market survey for design inspiration with comments posted online by users spontaneously, in an oral-near language, and almost free of biases. Opinion mining techniques are being developed, especially customer sentiment analysis. These techniques are most of the time based on a text parsing and costly learning techniques based on target or domain-dependent corpora for getting a fine understanding of users’ preferences. On the contrary, in this paper, we propose an overall sentiment rating algorithm, accurate enough to deliver an overall rating on a product review, without a tedious customization to a product domain or customer polarities. The developed algorithm starts by a text parsing, uses a Dictionary of Affect Language to rate the word tree leaves and uses a series of basic heuristics to calculate backward an overall sentiment rating for the review. We validate it on the example of a commercial home theatre system, comparing our automated sentiment predictions with the one of a group of fifteen test subjects, resulting in a satisfactory correlation.

With the emergence of environmental legislations in many countries, the importance placed upon environmental protection has been raised to a new level, especially for industrial activities. Considering environmental issues as early as possible, starting with the design stage, is expected in order to better manage and diminish adverse environmental impact. Commensurate progress has been made in method/tool development for use in environmental impact estimation. however, very few of these methods allow integrating this estimation early in the design process – a critical point of deciding for potential product concepts and suppliers. In this paper, we propose a tool that integrates environmental impact estimation into architecture and supplier identification, in order to conjointly consider requirements satisfaction as well as uncertainty due to new module and new supplier integration. This tool is developed to support OEM (Original Equipment Manufacturer) decision-making in the context of an extended enterprise. A case study is presented to illustrate a plausible implementation.

Addressing user needs and preferences is critically important in developing innovative and successful engineered products and systems. The task is inherently challenging due to the heterogeneity of user needs and the difficulty of modeling human behavior and preferences. In addition, it remains a challenge to integrate user preferences with technical and economic requirements during the engineering design process. The past decade has seen a significant growth in user-focused design research that introduces principles from different domains, such as market research, economics, cognitive science, and social science. However, there is still a lack of integration of these methods, either qualitative or quantitative, for directly supporting engineering design decisions. It is therefore imperative to develop interdisciplinary design approaches to address " interface " issues among different domains and engineering design, considering market demand, usage context, social behavior, environmental impact assessments, and other factors. With this in mind, we organized this Special Issue to gather state-of-the-art research in user needs and preferences, with the goal of identifying new research frontiers in this area. Over ninety technical papers were submitted for review to the Special Issue. All papers were subjected to a rigorous peer-review process with quality standards set by ASME. While the three of us served as associate editors for most of these manuscripts, we would like to thank Journal of Mechanical Design associate editor Dr. Christopher Mattson for his assistance coordinating the reviews of some of the papers. We are also very grateful to all reviewers who helped review these papers. This Special Issue collects fourteen papers including one technical brief. These papers are organized into four groups based on common themes: (1) User needs and preferences elicitation, (2) Incorporating user needs into engineering design, (3) Choice-based preference modeling and design, and (4) Modeling user behaviors and activities adapted to use contexts. The following summaries provide brief snapshots of these papers and the relationships between them.

Industrial systems (automotive, aerospace, etc.) are becoming more and more complex due to economic and ecological constraints. This growing complexity imposes new constraints on development. The question of mastering the analysis capacity of their architectures is then raised. To solve this issue, modeling and simulation tools have become a common practice in industrial environments afin order to compare multiple candidate architectures. These simulation tools have become essential to support decisions. Yet, the implementation of physical models is increasingly complex and requires a specific understanding of each simulated phenomenon as well as a thorough description of the system architecture, its components, and the connections between components. The objective of this thesis is twofold. The first concerns the development of a methodology and the tools needed to accurately build simulation models of the system architectures one wishes to study. The second is concerned with the introduction of an innovative approach for the design, production and integration of simulation models in a "plug and play" mode afin order to guarantee the conformity of the results to the expectations, especially at the quality and maturity levels. To accomplish these goals, model-based systems engineering (MBSE) methodologies and processes as well as information systems have been used. This thesis work proposes for the first time a detailed process and tool for the design of simulation models. A common repository named "Identity Card Model (ICM)" has been developed to standardize and strengthen the interfaces between the business and the suppliers on organizational and technical levels. MIC ensures the evolution and management of the consistency of the set of rules and the specifications of the knowledge of business domains with multiple semantics. MIC also reinforces model consistency and reduces anomalies that can interfere during the so-called IVVQ phase for Integration, Verification, Validation, Qualification. Finally, afin order to structure the simulation model design processes, the work drew on Enterprise Architecture frameworks by reflétant the integration and standardization requirements of the enterprise operating model. To validate the concepts introduced in this thesis, case studies from the automotive and aerospace domains were conducted. The objective of this validation is to observe the significative improvement of the current process in terms of efficiency, reduction of ambiguity and misunderstandings in the modeling and simulation of the system to be designed.

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An eco-industrial park is a set of businesses that share resources in order to increase profitability and reduce environmental impact. The implementation of eco-industrial parks may significantly contribute to the creation of a sustainable economy. Despite this prospect , the actual development of eco-industrial parks is challenging , as a variety of factors must be considered. Not only technical , economic , and environmental factors are relevant but numerous stakeholder relationships as well , such as between firms , governmental bodies , and local communities. This paper presents a conceptual framework that is used to capture these diverse aspects and the relationships between them. The Unified Modeling Language (UML) is used for modeling its concepts and relationships. First , based on a literature survey , relevant concepts of eco-industrial parks are identified. One central concept is " industrial symbiosis ". A novel value-based interpretation of industrial symbiosis is presented. Second , the park ' s economic , local and regional development context , as well as its internal technical components and their relationships are modeled. Finally , the framework is used for modeling a concrete eco-industrial park , in this case part of the Kalundborg eco-industrial park .

In a multidisciplinary virtual prototype development project, OEMs (Original Equipment Manufacturers) take the responsibility of requirement specification, system design, and Integration and Verification and Validation (IVV) steps. This is followed by the supplier, which develops the domain level simulation models. Although the simulation model is tested at the supplier level and the OEMs are responsible for the final integration, system and acceptance testing to ensure that the given implementation of a system level simulation model meets its intended goals. However, in current system IVV practices, OEM detects any kind of inconsistencies problems during final integration stage. This significantly increases the risk that errors are found late in the development process. This may create unexpected rework that negatively affects cost and schedule. The aim of this work is to reduce the late inconsistency detection by ensuring the early stage collaboration with a clear simulation model request and design artifact negotiation. For this aim, this paper proposes an early stage virtual prototyping design that contains the formal system architecture design, Model Identity Card (MIC) and Model of Intention (MoI) concepts. An industrial case study is used to show how such mentioned early stage virtual prototyping might reduce the knowledge gap and inconsistencies problems between OEMs and model providers.

Usefulness, from the utilitarianism perspective, is the ability of a product or service to improve the well-being of humans and to minimize their suffering in different situations. In the case of the widespread issue of falls among the elderly, designing an adapted solution to is not an obvious task. The latter requires quantifying various usage scenarios. The usage scenarios, or segments, associated with elderly falls must be investigated to ensure that newly designed products and services are likely to bring essential health, social and economic values. Optimizing a design solution by considering the coverage of such usage segments extends the classical methods of design for market approaches. Starting from a disparate literature on elderly falls' issue, we have first built a usage scenarios space. Next, the usefulness and the coverage ability of three design solutions are evaluated over a tessellation of usage segments. In addition, the developed usage simulator is used to assess the potential of non or poorly-covered usage segments to deliver insightful information in order to truly be a need seeker in the front-end of innovation.

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You have started to structure an innovation project from an initial idea. Knowing the users, or more broadly the beneficiaries of the product or service you want to develop, is absolutely essential. Yet few project leaders today really take the time to observe. This sheet will enable you to understand the importance of observation, but also of the representation of uses by defining a protocol in adequacy with your objectives. You will then be able to analyze the results and choose a suitable representation mode to formalize and capitalize on your experience, but above all to bring to light the problems and pains of the users and thus convince the decision-makers of the accuracy of your reasoning. Observation and representation of uses is the third deliverable of the Radical Innovation Design® (RID) methodology, described in detail through various practical sheets. After structuring the project and defining the ideal need, this deliverable allows to really get into the uses, problems and pains of the users or beneficiaries, linked to the existing products and practices. It allows to initiate a thorough analysis of the uses and problems in order to uncover pockets of value, significant combination of a problem and a use not or poorly covered by existing solutions.

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Occupants’ behavior exerts a significant influence on the energy performance of residential buildings. Industrial energy simulation tools often account for occupants’ as monolithic elements with standard averaged energy consumption profiles. Predictions yielded by these tools can thus deviate dramatically from reality. This paper proposes an activity-based model for forecasting energy and water consumption of households, and discusses how such an occupant-focused model may integrate a user-focused design of residential buildings. A literature review is first presented followed by a brief recall of the proposed modeling methodology and a sample of simulation results. The possible integration of the proposed model into the design and energy management processes of residential buildings is then demonstrated through a number of use cases.

Driven by a utilitarian perspective, the question of useful innovation and creating essential values is set. Such innovation should lead to cover or alleviate significant pains which are not satisfactorily covered by existing solutions. Radical Innovation Design (RID) is a structured methodology for exploring the front end of useful innovation in need seeker mode. In this paper, the fundaments of RID are presented for the first time and illustrated on the search for radical innovations for a handitennis wheelchair of a champion. The most original part of RID stands in the problem setting stage which starts with re-expressing the ideal need to set the issue playground-for usefully thinking in the box-in which two worlds are populated: the world of problems or pain points and the world of usage scenarios. The determination of value buckets has been automated by matrix representations of dependencies between problems, usage scenarios and existing solutions. A subset of opportunistic value buckets are further addressed in the problem solving stage for focused ideation, to ensure performing " blue ocean " innovations, i.e. in not yet explored usage and problem situations.

The globalization of markets, the rapid growth of emerging countries, the challenge of sustainable design of products and services, and the needs of low-income populations are all issues that are prompting companies to seek new forms of organization and innovation in response. The Base of the Pyramid (BoP) theory is part of this current context and proposes to contribute to the fight against poverty while following an economic logic. Although it is relatively recent, the literature on this theme is multiple and is now mainly in management sciences and economics. The contributions in the field of engineering are still quite limited and many questions remain unanswered about the feasibility and operationality of such an approach. The objective of this research work is to understand how the dynamics of innovation oriented Base of the Pyramid require a rethinking of current design practices, especially frugal engineering. This design process, which integrates economies of use and expenditure, is explored as a means of designing products and services in the dual context of poverty alleviation and economic profitability. Our contributions are based on two axes. The first is based on a study of 215 cases of BoP innovation reported in the literature to propose a categorization of BoP strategies. This categorization gives rise to a multi-level reading and allows us to identify important findings: the difficulty of combining social impact and economic impact in the same approach, the marked dichotomy between market strategies and inclusive strategies, as well as the existence of multiple BoP contexts that reflect a tension between satisfying needs (local impact) and the search for a change of scale (global impact). The second axis of contribution concerns frugal design, taken as a possible approach oriented Base of the Pyramid. We define frugal engineering as the search for the right balance between the proposition of an essential value and the search for a low cost. The proposal of new concepts, such as the "Non Trade Off" of the design process and the "Adaptability" of a product, leads us to question the uniqueness of this just-sufficient. The essential value is not an absolute and unique concept, but is declined in a multitude of values (re)defined by the appropriation of the product during the design, the manufacturing and the use. This appropriation involves strategies to focus on essential functionalities, so as to be able to respond to an environment that is poor in resources and infrastructure, to reduce production and assembly costs, and to meet an essential need. Frugal design is then part of an inclusive logic, where each stakeholder in the value chain contributes to redefine the just-sufficient of a frugal product according to the context. These results, from empirical fieldwork in India and Vietnam, allow us to emphasize the importance of taking into account elements of the contextual environment in the design process. We propose to represent these elements in the form of Scenes, to complete the existing user-centered tools, and to contextualize the reflection on the essential value of the product. To conclude, from these results emerge the premises of an open model of frugal design that would leave more flexibility to the Base of the Pyramid populations to appropriate the essential value of the designed product. Designing open products, adaptable to the variability of contexts, thus makes it possible to work towards a more sustainable development.

The building sector is considered a major energy consumer and source of pollution among all economic sectors. It accounts for between 16 and 50 percent of national energy consumption. Reducing energy consumption and emissions is therefore an important step towards sustainable development. Recently, the transition to low-energy building construction has led to new performance and sustainability requirements, and thus further complicated the building design process. The behavior of the occupants is now considered as a determining factor of the energy performance of a building, especially in the case of low energy buildings (BBC). However, the simulation tools used in the building industry are not currently able to provide reliable estimates of occupant energy demand. Therefore, energy and building experts are paying great attention to developing more accurate methods for modeling and predicting the influence of occupants on building performance. These models must be able to provide more accurate estimates of energy consumption and assess the variability of these consumptions. Consequently, the objective is to allow building experts to improve their technical solutions, to improve the performance of their services, and to promote better targeted incentives to users in order to reduce their energy consumption. The objective of this thesis is to propose a model to estimate the energy consumption related to the behaviors of the occupants of residential buildings, taking into account the variability of consumption patterns through the diversity of socio-demographic and economic profiles of the occupants. A stochastic approach based on the notion of activity is therefore adopted. With this model, the energy consumption of a household is estimated by adding the energy consumption of the different domestic activities (such as cooking, washing clothes, etc.). The stochastic nature of the model is due to the probabilistic relationships established between household attributes on the one hand (household type, number of occupants, etc.) and the ownership of household equipment, appliance characteristics, their power, and activity quantities on the other hand. In order to establish these stochastic relationships, a sufficient number of attributes are taken into account to characterize a household. The proposed model has been applied for two household activities, namely watching television and washing clothes. Monte Carlo simulations are performed to provide energy consumption estimates for these two activities in three cases: for a specific household, for randomly generated households with constraints on their attributes, and for completely random households representative of the French population. A comparison between the results of the model simulation on the one hand and real energy consumption data on the other hand, allowed to validate the model for the two activities considered. A framework for the generalization of the model for other domestic activities was introduced, and its possible integration in the building design process was discussed and illustrated through a number of examples.

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What industrial company doesn't dream of improving its competitiveness in the long term? Incremental or disruptive innovation is seen as a strategic way to win new market share, or at least satisfy and retain customers. More than any other, Airbus Helicopters is investing and innovating in its products and services. A new axis is now emerging: engineering innovation, which includes processes, methods and tools for product design and certification. Engineering innovation is part of a "lean engineering" approach. Investing in innovations does not guarantee an impact on competitiveness. It is necessary to aim for the success of the innovation, i.e. to ensure, at each phase of the process, that the innovation meets the initial objectives, the upstream phase initiating the innovation process. This thesis examines how to structure and manage feasibility studies for incremental engineering innovation, in order to anticipate success from the upstream phase. Based on a diagnosis of industrial practices, a methodology for steering engineering innovation in the upstream phase is proposed. This methodology is based on a typology of upstream projects, a typology of stakeholders, a process accompanied by methods and tools. The steering process is articulated with a system engineering approach. A first phase of specifications is based on the modeling of usage scenarios, and a second phase of verification and validation is punctuated by an evaluation of the value. We propose to pilot an engineering innovation by evaluating its functional value, its utility, its profitability and its strategic value. The steering methodology is formalized by a UML model, which can be used to manage a portfolio of upstream projects.

Integration and coordination of engineering analysis model is a vast development field in the context of complex product development. Engineers' siloed way of working in combination with lack of efficiency in current model development process may cause inconsistency based on model interfaces, human errors, miscommunication between teams and misinterpretations. In lean terms, this may create multiple wastes, including waiting, overproduction leading to excess inventory, unnecessary processing and may be the most harmful: defects (e.g., incorrect models) with rework consequences. Hence, product manufacturing companies must establish effective processes to add value throughout the multidisciplinary distributed modeling environment. The goal of this paper is to propose a pull-control model development process, providing model architecture integration and coherent control in early design phase. This paper proposes also an appropriate reuse strategy. this allows for utilizing plug-and-play type modular product models managed through a single-source of authority concept. A pull-control development process helps prevent potential rework arising from inconsistencies related to definitions, know-how and stakeholders communication at an early stage of the design process. Also, the proposed black box models reuse strategy helps reduce human-related error such as lack of domain knowledge, experience and misinterpretations. The proposed method is used to identify and visualize potential improvement in terms of increased model transparency and reuse when transforming from the present to the suggested future modeling strategy. The research has been conducted by synthesizing findings from a literature review, in combination with observations and analysis of current analysis model development practices within the automotive OEM Renault in France.

Today it becomes necessary for manufacturers to adopt Eco-design to guard their place in the market. Eco-designing products, is reducing their environmental impact in the early design stages throughout all stages of their life cycle (raw material extraction, manufacturing process, use, transport and end of life treatments). In the literature, many tools and methodologies were developed to simplify the environmental task to the designer by helping him reduce the environmental impact of his products. The most of these works are based in feature-based modeling to extract data for realizing environmental evaluation (EE) also we found that this technology is essentially used in selecting a green machining process through Computer Aided Process Planning (CAPP). In this paper we propose a methodology based on feature technology and on the integrations realized on CAD systems such as CAD/CAM/CAPP and CAD/PLM to generate alternative scenarios in order to choose the most ecological one till feature’s selection. The environmental impact is calculated with CML method and shown to the designer as End-Points Indicators (Resources, Human Health, Eco-system damages) which are related to the designer’s Degrees of Freedom (DoFs). A case study was considered to valid our proposed approach and results are shown and compared to results obtained from SW sustainability and a complete LCA from SimaPro integrations.

The objective of this thesis is to establish an eco-design method based on Life Cycle Assessment, which should allow the identification of environmental action levers specific to each of the different economic actors involved in the life cycle of a product. The Life Cycle Assessment was coupled with two sensitivity analysis methods, following five steps described in the thesis: (i) the definition of the objectives and the system, (ii) the modeling of the calculation of the inventory and the impact indicators with differentiated approaches in the foreground and background, (iii) the characterization of the parameters used with a defined typology according to the possibilities of action of the economic actor concerned, (iv) the successive realization of two methods of sensitivity analysis (Morris and Sobol) on the defined model, (v) the interpretation of the results with a view to proposing effective avenues for improvement. The established approach was applied to the life cycle of hemp concrete, with the study of the stages of agricultural production, processing of hemp fibers and use of hemp concrete as thermal insulation in buildings. The approach allows to identify potential technological scenarios, allowing to improve the environmental performances, for each of the actors of the life cycle of the product. Implementing this approach currently requires additional information, but has a long-term gain as it allows to make robust choices for a given product.

Interface definitions are important in complex system design, as they contribute to the definition and satisfaction of functional flows. Design Structure Matrix approaches have only recently focused on integrating possible interface types in conceptual design. In order to address the issue of interface definition, a physical interface data model is proposed in order to define the interface design space. Moreover, this data model is integrated into complex system architecture definitions in order to support collaborative conflict detection. The data in the physical interface data model is used as a basis for risk identification in the collaborative design space and associated shared design parameters.

Building occupants are considered as a major source of uncertainty in energy modeling nowadays. Yet, industrial energy simulation tools often account for occupant behavior through some predefined scenarios and fixed consumption profiles which yield to unrealistic and inaccurate predictions. In this paper, a stochastic activity-based approach for forecasting occupant-related energy consumption in residential buildings is proposed. First, the model is exposed together with its different variables. Second, a direct application of the model on the domestic activity “washing laundry” is performed. A number of simulations are performed and their results are presented and discussed. Finally, the model is validated by confronting simulation results to real measured data.

The resolution of complex design problems requires a distributed design system that considers the involvement of various designers. Inconsistencies of design objectives and working procedures of distributed subsystems can cause design conflicts due to couplings among their subproblems. Another issue is the management of imprecision in design systems caused by the lack of knowledge about the final decision. In this paper, we define a conflict management model using the concept of set-based design to overcome these issues. We utilize constraint satisfaction problem (CSP) techniques and model agent attitudes to detect and justify design conflicts of heterogeneous design agents. A novel cooperative CSP is defined for resolving design conflicts through compromising constraint restriction. The conflict resolution system can be adopted with different strategies which take into account the solidarity architecture of design agents. The gains and costs of centralized, decentralized and controlled conflict resolution system strategies are simulated with the Monte Carlo method where design agent characters and their interactions reflect a stochastic nature.

The Dependency Structure Modelling Value Bucket (DSM-VB) tool is integrated to Radical Innovation Design (RID) methodology for exploring the front end of innovation in need seeker mode. The determination of value buckets has been automated by matrix representations of dependencies between problems or pain points, usage situations and existing solutions. Three matrices are built along the problem setting stage of a RID process. The first matrix expresses which problems occur during usage scenarios, the second how much existing solutions cover problems and the third how much existing solutions are useful in usage situations. Combining these three matrices results in a matrix of value buckets as being the combinations of important problems occurring during characteristic usage situations and for which few existing solutions are useful or efficient. This outcome allows to perform focused creativity workshops and to result in " blue ocean " innovations with high likelihood to be successful on the market.

For more than 10 years, the French State and administrative regions have pursued economic development policies that stimulate all forms of innovation and encourage strategic market alliances of the economic stakeholders of a region. These “cluster” policies aim to create ecosystems that are conducive to innovation and promote the emergence of collaborative organizations. Among these innovation clusters, we are concerned with those in the health care field pertaining to aging and autonomy. Business models and action plans for these collaborative organizations are neither easy to define nor easy to stabilize and reinforce, because of the diversity of stakeholders with multiple expectations involved. This paper presents an application of the FAcT-Mirror method in the Sol’iage innovation cluster during its development stage. We demonstrate that the FAcT-Mirror method is particularly efficient and effective during the process of transformation from the emerging stage (stage of intention) to the development stage (stage of action) for a health care cluster to collectively produce common tools (definitions, strategy, working groups, and action plans).

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In distributed design systems, while designers are connected to each other through dimensioning couplings, they have limited control over design and performance variables. Any inconsistency among design objectives and working procedures of heterogeneous designers interacting in the design system can result in design conflicts due to these couplings. Modeling design attitudes can help to understand inconsistencies and manage conflicts in design processes. We extend the conventional bottom-up or design supervision approach through agent-based attitude modeling techniques to a more powerful level. In our model, design agents can set requirements directly on their wellbeing values that represent how their design targets are likely to be met at a given moment of the design process. Some design conflicts can in this manner be prevented at an earlier phase of the design process. Set-based design and constraint programming techniques are used to explore the overall performance of stochastic design collaborations on a product modeled with uncertainties at a given moment of the design process. Monte Carlo simulations are performed to evaluate the performance of our set-based thinking approach, providing a variety of agent attitudes. The results show that the number of design conflicts occurring during the design process and the intensity of design conflicts are both reduced through our collaborative design platform.

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While many product properties can be tested objectively, others are subjective, but no less important. This paper compares how the testing of subjective properties is handled across industry sectors. Engineering companies typically try to break these properties down into measurable aspects of the product, but refer to the judgement of test engineers for emergent properties. By contrast the fashion industry sees the assessment of subjective properties a core competence of designers. The food industry also tries to measure objective properties, but relies heavily on user and expert panels.

High-tech mechatronic system design, such as for tools for oil-well drilling and exploitation, requires that engineers from multiple domains concur on architectural solutions due to a large number of interdependent system performance criteria and design parameters that are shared across architecture interfaces. Supporting designers in envisioning probable challenges in architectures early in design is of utmost importance to ensure project quality while minimizing costs and delays. In this paper, we present the Multiple-Domain Design Scorecards (MDDS) method to facilitate architecture generation and assessment through architecture interface characterisation as well as to support design process management. We propose to semantically enrich the Design Structure Matrix (DSM), Domain Mapping Matrix (DMM) and Quality Function Deployment (QFD) representations to capture project data and expertise related to concept generation. In addition, we propose six types of Design Assessment Cards (DACs) that both support design space exploration and highlight design challenges of potential system architecture. The proposed approach is being implemented and tested in an industry context. A case study in the oil industry brings to the fore some of the advantages and challenges in the implementation process.

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Monitoring industrial systems in real time raises some cognitive problems especially due to the important number of alerts that must be aggregate by the monitoring system itself and prioritized by operators. Among other senses (vision and sound), color may bring valuable insights to operators for quickly understanding alerts and appropriately react. In our case of supervising interfaces in real time of oil exploitation, the operators have safety constraints concerning environment, machines and human. It is necessary to bring into focus the situation quickly to the operator so that he/she acts. In order to assist the operator during his/her activity and to limit his/her cognitive effort, the supervision interfaces are equipped with alerts which have several important levels like "danger", "critic", "weak anomaly" or "no problem". We perform an experiment focuses on the comparison of three alert colour tested on a supervision interface by users used to this interface types. Our results prove that one alarm color code is 47% more efficient in terms of time reaction of testers. This best colour is a "red gradation" i.e. from bright red for the "danger" alert to white for the "no problem" alert. This alert type is not only efficient for the supervision, but also for a strategic or piloting dashboard, even personal dashboard as personal expenses management.

Residents' usages and behavior play a determining role in the variability of the energy consumption and environmental impact of residential buildings during their use-phase. At present, however, they are inadequately documented and understood, as well as being highly variable. In this paper, we propose a use-phase memory model for residential buildings, whose aim is to store energy consumption and usage patterns. This storage can be done automatically or voluntarily. We give examples of useful information extracted from the data captured. The objective of this data analysis and synthesis is to provide building experts two specific use-cases: designing a new sustainable building, and renovating an existing one. Our model is deployed on a residential building, integrating the beneficial services for all stakeholders to demonstrate a sustainable relationship between designers, the residential building and the users.

Functional Unit (FU) ensures the consideration of comparable product quantities to provide reliable Life Cycle Assessment (LCA) results.

In distributed design, in the product sizing phase, inconsistencies may emerge between design goals and between the work procedures of heterogeneous subsystems. In this phase, the design actors must collaborate in a concurrent manner, as their tasks are linked to each other by the design couplings between their sub-problems. Inconsistencies can cause design conflicts due to these couplings. The question is how to achieve collaborative convergence to satisfy the global and individual goals of design actors when these actors make design decisions under uncertainty. The objective of this thesis is to propose a model to prevent and resolve design conflicts, while overcoming the problem of design uncertainty with the "set-based design" (SBD) approach. For this purpose, design attitudes are modeled with the "Beliefs-Desires-Intentions" paradigm to explore inconsistencies and manage conflicts in design processes. The conventional bottom-up approach is thus extended with multi-agent modeling techniques. In this approach, design agents can set requirements directly on their "well-being" indicators. These indicators represent how their design goals are likely to be satisfied at a given point in the process. Monte Carlo simulations are performed to evaluate the performance of this approach, offering a variety of agent attitudes. Compared to traditional bottom-up and top-down design approaches, the results reveal fewer design conflicts and reduced conflict intensity. Constraint satisfaction problem (CSP) techniques and design attitudes are applied to detect and justify design conflicts between heterogeneous agents. A new form of the Cooperative CSP (CoCSP) model is thus developed to resolve design conflicts by detecting the trade-off between constraints. The conflict resolution system can be adopted through different proposed strategies that take into account the solidarity architecture of the agents. Simulation results show that the intensity of conflicts in distributed design is reduced by promoting solidarity that triggers help to suffering agents.

As with other European countries, the French automotive industry needs to improve the End of Life Vehicle (ELV) recycling rate in order to reach the minimum reuse and recovery rate required by EU directives. This paper proposes a model to investigate the potential cost and benefit of ELV glazing recycling for all value-chain stakeholders, and for the network as a whole. Key parameters of future changes, namely glass cullet price, landfill cost, network coverage and transportation costs are identified at the level of field research. A system dynamics approach is then used to model the Cost-Benefit Analysis (CBA) and to simulate the effect of changing these parameters on the cost and benefit of the glazing recycling chain. The simulation reveals an increase in the income and considerable cost savings as a result of the recycling network of future scenarios.

While the marketing literature has advocated for decades that new products should be designed for intended and anticipated consumer usages, the engineering literature mostly proposes optimization of product performances independent of specific users' skills, anticipated usage scenarios, and competing products on the market. In contrast to tedious market studies which assume an existing market experience for products and optimization approaches based upon static product performances, we propose an adaptable approach to designing a product or product family: the set-based design by usage coverage simulation. It starts with generating a usage scenario space for a set of representative users. Next, considering a candidate set of products, one proceeds to the CSP computations of feasible usage scenarios, assuming that physics-based models of performances are available. The comparison between the expected and feasible usage scenarios at the scale of a single user leads to Usage Coverage Indicators and finally to a preferred product which best covers the usage scenario space. At the level of a targeted consumer group, the approach provides a market share simulation for competing products or members of a scale-based product family. The design of a family of jigsaws thoroughly illustrates our approach.

Residents’ usages and behaviour are inadequately known and understood, as well as being highly variable. However, they play a determining role in the variability of both the energy consumption and environmental impact of residential buildings during their use-phase. This paper proposes a use-phase memory model for residential buildings, which stores energy and resource consumption, and usage patterns. Useful information is further extracted by data crossing and visual data representation. Building experts refer to it for two specific use-cases, namely designing a new sustainable building and renovating an existing one. This information helps them to understand energy and resource consumption and, real users’ behaviour and activities. Building’s users obtain different kinds of service in return for their collaboration and contribution. Our model is presently being deployed on a residential building, based on beneficial services for each building’s stakeholder, thus introducing a sustainable relationship between designers, the residential building and its users.

Value chain concept and methods has assumed a dominant position in studying industry from management point of view. Decision supports methods using value chain require the acquisition of data from various existing corporate databases or data warehouses. In design research discipline, the subject of value chain design is emerging. Only a few of published research took a wide scope comparable to theories used today in engineering design. As an effort in developing the methodology and as a result of research within a national industrial consortium, this paper proposes and discusses a general value chain design approach which opens up a promising perspective to provide a new direction for research and application of value chain from scratch for multi-stakeholder industrial systems. It introduces value chain design as a way to determine, model, and analyze and evaluate the industrial ecosystems, in order to generate future scenarios and provide evaluation criteria for decision makers. To illustrate its application, the establishment of end of life vehicle recycling subsidiary at national level is explored to identify potential values stakeholders.

Creating a new recycling system generally suffers from the lack of a coordinated group of stakeholders rather than technical issues of treatment, or available recyclable deposit. Value chain concept and methods has assumed a dominant position in studying industry from management and coordination point of view. Decision support methods using value chain require the acquisition of data from various existing corporate databases or data warehouses. As an effort in developing a methodology and in result of conducting a national industrial recycling chain in France, this study proposes a general value chain design approach which provides a new direction for research and application of value chain from scratch for multi-stakeholder industrial systems. This paper introduces value chain design as a way to determine, model, and analyze and evaluate the industrial ecosystems, in order to generate future scenarios and provide evaluation criteria for decision makers.Copyright © 2013 by ASME.

The integration of environmental aspects in design frameworks has become a necessity for manufacturers to maintain their market position. This is especially true in the Computer Aided Design (CAD) phase, which is the last phase in the design process. At this stage, more than 80% of choices have been made. However, the environmental impacts generated by the remaining choices are significant. Features Technology (FT), the core of the CAD phase, is used to integrate environmental aspects. This paper presents a literature review of different works based on FT to ecodesign products. First, we present an overview of features in CAD systems. Second, we present a critical review of works done on ecodesigning with features that we divide into two subsections: the first one concerns CAD-Life Cycle Assessment (LCA) integration (methodologies, prototype tools, and commercial tools), and the second one, works using FT in CAD phase to reduce the environmental impact of one life cycle stage such as material selection or.

Assessing the number of users defined by a set of specific usage attributes in a given usage contextual situation is not always an obvious task in a market segmentation process. Although new approaches in design and marketing seem to be more sensitive to the adequacy of a design concept with the usage scenarios, these methods do not systematically consider the various usage situations. The present article puts forward a methodology intending to build a usage scenarios space in which the input data is thoroughly collected and validated. This methodology is applied to the complex and multifactorial issue of falls among the elderly in the Metropolitan France. In this paper, numerous medical publications have been made to study influential factors of fall situations. However, even solution providers for fall prevention and teleassistance ignore the real situational coverage of their solutions. As a result, “usage scenarios space” is built using an appropriate segmentation of usage contexts (here, fall situations) and user characteristics. These data are used for a design oracle to predict (simulate) the various and multiple usage scenarios.Copyright © 2013 by ASME.

The aim of this extended editorial is to offer a perspective on design creativity and innovation research on the occasion of launching the International Journal of Design Creativity and Innovation. Thirty six members of the editorial board present their expectations, views, or opinions on the topics of the journal. All of these articles are presented in Section 2. In Section 3, summaries of the 36 articles are consolidated. This editorial also analyzes keywords from each of the articles, and the results are visualized in Section 4. The keyword analysis covers not only those words taken directly from each of the articles but also the implicit keywords that are suggested by the explicit ones. We believe this extended editorial will help the researchers, in particular young researchers, comprehend the essence of design creativity and innovation research and obtain a clue to tackle the new discipline.

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In a recycling scheme such as the recycling of End of Life Vehicle (ELV) materials, the different takeholders are expected to configure the operation process and product distribution to maximize their own profits. In many cases, however, these individual optimizations do not correspond to the maximal profit for the whole chain. In addition, financial autonomy must be carefully studied and controlled so as to ensure an conomically viable recycling chain. This paper proposes a cost-benefit parameterized model for the ELV glazing recycling scheme, both for network configuration and material flow sizing. The model is mapped using real ground data from French industrial partners, and a linear programming technique is used to optimize the network for maximum profit. The sensitivity of this economic performance in different situations is analyzed by varying key variables of the model. Results show that, while the current glazing recycling situation is not economically viable, a national glazing recycling network could actually become beneficial for all stakeholders under certain conditions that are likely to appear in the near future. Several scenarios for the recycling network are simulated to determine the best practices for each of the network scenarios.

In distributed design systems, designers are related to each other through couplings, however they have limited control over the design variables. Any inconsistency in the design system can result in design conflicts through these couplings. Modeling designer attitudes can help to understand inconsistencies and manage conflicts in design processes. We expand the bottom-up design approach through agent-based modeling techniques to another level where designers can make decisions directly on their wellbeing values that represent how their desires are satisfied. Set-based design and constraint programming techniques are used to explore the imprecision of the design activities. Monte Carlo simulations are performed to evaluate the performance of our approach. The results show that the number of design conflicts and their harshness can be lowered when the design process is defined with our approach.Copyright © 2013 by ASME.

In new complex product development processes, the design problem is usually distributed to multiple actors from different disciplines. Each design actor has a limited responsibility in the design system. Therefore, each design actor has limited control over design variables and performance variables. However, design actors are not isolated since their design activities are coupled. This can generate design conflicts through inconsistencies among design objectives and working procedures. When the design convergence is not controlled, inconsistencies can distort the satisfaction equilibrium between design actors. This means that if a design actor aims at satisfying only his/her local design objective, other actors having conflicting objectives will be dissatisfied. Thus, individual satisfactions diverge. The intensity of conflicts is measured with the satisfaction divergence. In this paper we define wellbeing indicators in order to control the convergence of distributed set-based design (SBD) processes. Wellbeing indicators reflect design actors' satisfaction degree of their process desires. We performed a constraint programming Monte Carlo simulation of our SBD framework with a complex design problem. We compared the results of wellbeing indicators with the results of the processes where design actors do not use wellbeing indicators. It is shown that when design actors have some means to control their convergence, the solution space converges to a solution in satisfaction equilibrium while epistemic uncertainty of the design model is reduced. Some conflicts are therefore prevented and the satisfaction divergence is reduced, leading thus to an improved design process performance.

In this paper, we investigate the impact of product, company context and regulatory environment factors for their potential impact on medical device development (MDD). The presented work investigates the impact of these factors on the Food and Drug Administration's (FDA) decision time for submissions that request clearance, or approval to launch a medical device in the market. Our overall goal is to identify critical factors using historical data and rigorous techniques so that an expert system can be built to guide product developers to improve the efficiency of the MDD process, and thereby reduce associated costs. We employ a Bayesian network (BN) approach, a well-known machine learning method, to examine what the critical factors in the MDD context are. This analysis is performed using the data from 2400 FDA approved orthopedic devices that represent products from 474 different companies. Presented inferences are to be used as the backbone of an expert system specific to MDD.

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Reducing the environmental impacts of products surrounding us in our daily lives has become a common concern for the industry as well as for consumers. The practice of a Life Cycle Assessment (LCA) allows determining not only the environmental impacts centers but also the overriding factors on which it is still possible to act at the design phase. The geometric modeling phase in the design process represents an important step to make the necessary changes on the product in order to reduce its environmental hotspots. In this paper, we have eco-designed a basin mixer by acting on its geometric modeling phase, after identifying its various environmental hotspots from a LCA practiced and determining the factors still editable on CAD phase. An environmental comparison between the eco-designed mixer and the original one has been established, which shows a 66% reduction of impacts linked only to the amount of material used.

Purpose: This paper considers the variabilities that exist in the exploitation of a complex industrial system. Our scenario-based LCA model ensures the reliability of results in situations where the system life cycle is very uncertain, where there is substantial lack of data and/or where time and resources available are limited. It is also an effective tool to generate exploitation recommendations for clients. Method: Existing quantitative uncertainty methods in LCA require a huge amount of accurate data. These data are rarely available in simplified and upstream LCA for complex industrial systems. A scenario-based approach is the best compromise between acceptable quality of results and resources required. However, such methods have not yet been proposed to improve the environmental knowledge of the system in the case of exploitation scenarios. The method proposed here considers a limited number of scenarios (3 or 4) that are defined using the Stanford Research Institute (SRI) matrix. Using results from past projects, relevant parts of the system are listed, and expert knowledge and parameters are associated with these parts and quantified. A classical LCA process then provides the results for the different scenarios. Results and discussion: The method was applied to an Alstom Grid AC/DC conversion substation for the primary aluminium industry. A previous study had limited scope, as the life cycle was poorly understood. Relevant parts were thus clearly identified: spare parts program, transport failures, preventive and corrective maintenance, updates and revampings, lifetime modulation and end-of-life. Four scenarios were considered: best case, worst case, baseline (expected future) and a highly different alternative. Results show the pertinence of considering several exploitation scenarios when the life cycle is not predictable, as the environmental impacts may vary widely from one case to another. A sensitivity analysis also shows that some relevant parts such as updates and revampings will need to be carefully considered in futures studies. Conclusions: The consideration of three exploitation scenarios (best case, baseline and worst case) appears to be extremely pertinent when considering simplified LCA of industrial systems with high uncertainties and limited time and resources. This model is also very useful to generate good practice and recommendations towards clients, thus initiating a dialog centred on eco-design and continuous improvement.

It is common in the Management Science and Design Engineering communities to represent the processes contributing to innovation in companies as a funnel or similar variants. It is assumed it is possible to represent an analogy to the stages of planning and idea generation (the so-called fuzzy front-end), conception generation, as well as idea and concept selection to end up with the very few emerging developed and launched products and services on the market. First, this analogy may feature different innovation process layers, each of them independently as well as the entire set of these innovation process layers. After a review of literature on this funnel representation, we show that this analogy may be meaningful to globally represent and discuss about some properties of the innovation capability of a company at different locations: the R&D process as well as a given NPD process. We further describe a survey carried out within 28 large European technological companies through 48 detailed face-to-face interviews. Our questionnaire has allowed us to observe some characteristic patterns in the innovation funnels. We finally propose a model of five innovation funnels varying by their shape, permeability of emerging ideas and agility in terms of innovation management. We also hypothesize that these 5 funnels evolve in a sequential and cyclic way and that our cyclic model may be used as a questioning tool for the continuous improvement of the innovation management.

Studying design creativity and innovation from practical perspectives for companies requires both a good understanding of the company ecosystem and its inner processes contributing to delivered innovations and a rigorous design research methodology to provide effective design models, methods, platforms that are truly effective in the context of company. Working in an Industrial Engineering laboratory, we advocate a more systemic vision of design creativity and innovation in company ecosystems. We present in this paper an attempt to develop and make professional an innovation engineering. Our research works are illustrated along the different research topics of an innovation process. We start by a recent survey on innovation practice and organizational models led in 28 large companies. The lessons learned about this survey reinforce our belief that there is a need for a new method in agile management of radical innovation projects in company contexts. We currently develop, test and apply such a methodology named: Radical Innovation Design® (RID). Its effectiveness has been evaluated through a large scale evaluation of the project outcomes for the company. Two extensions of RID have been proposed and deployed in company contexts: a selection procedure for innovation clusters and a value-driven process for airplane development projects.

The development of product-service innovation projects within the context of a company is not yet supported by clear theories and methodologies. Our objective is to analyze innovation and idea generation for such projects from the fuzzy front end to the selected design concept, assessing their potential to be successfully developed and launched on the market. We present a protocol study, using which data derived from 19 innovation projects of five types and conducted by 86 students are analyzed. Sixty-one variables are observed, thus generating 700 data vectors. Bayesian network learning is used to explore conditional inferences among these variables. We examine conditional probabilities between the innovation process means and the significant results produced for the company, modulated by the influence of contextual variables. A number of surprising findings are drawn about the link between problem setting and problem solving processes, the importance of certain contextual variables, and the potential discrepancies between the apparent and produced results of innovative projects. Conducted analyses imply the need for novel innovation evaluation frameworks.

Residential buildings are seen as major energy consumers among other industrial sectors worldwide. As we move towards low-consuming and nearly zero energy buildings, higher performance requirements on sustainability and robustness are manifested. Consequently, a better comprehension and integration of building performance determinants in the very early phases of design has become essential for building constructors. Buildings experts rely on energy modeling and simulation tools for estimating actual and future energy consumptions. However, such tools still do not account precisely for occupant behaviors and their variability, yielding thus to unrealistic and inaccurate results. Therefore, it is assumed that a better comprehension of occupant behaviors and their consumption trends could improve the identification of technical solutions and energy saving potentials, resulting consequently in more robust building designs. In our research work, we aim to develop a model for forecasting the spectrum of occupant-related energy consumption in residential buildings. In this scope, we establish a comprehensive model-driven approach which gives a probabilistic mapping between household profiles and their corresponding domestic energy consumptions. A bottom-up model using an activity-based approach is adopted. In this paper, we present the structure of the model, reveal its different objects together with their interactions, and introduce its ontology. Later on, we demonstrate the modeling and simulation flows leading to calculate the energy consumption for example household types.

In 2011, France is the second European food producer after Germany with a production value of 151 billion euros which is mainly based on the transformation of 70% of its agricultural production (Ministry of Agriculture, Agri-Food and Forestry of France, 2012). France, however, lost the European leadership it held for decades in favor of Germany. In this hypercompetitive market situation, innovation is defined as the only solution for a differentiation besides cost reduction. However food innovation results in many failures: it is commonly accepted that the failure rates (withdrawal of the product from the market after one year) be in this sector of 70% (Anon, 1999). In the work presented here we focus on the organization implemented by food companies to support their innovation process and the relationships between the actors involved in it, particularly on the collaboration between the marketing and R & D. This model is supported by the synthesis of interviews conducted in different food enterprises with actors of the food innovation process.

Eco-innovation methodologies and tools are increasingly applied in companies, but none of them is really adapted to the consideration of complex industrial systems. These systems are characterized by their large size and mass, and their particularly long and uncertain life cycle. We propose in this paper an adapted eco-innovation process, based on the Brezet eco-design strategy wheel. This process is built around a group of technical experts from the company. In a first phase, a large number of potential R&D projects are generated from LCA results, then analyzed and evaluated using an adapted multicriteria grid. Three filters are then used to select the most promising projects in order to build a balanced portfolio of R&D projects. The whole approach has been applied at Alstom Grid on AC/DC conversion stations used in the primary aluminium industry. With very limited time and resources, more than 100 ideas were generated to finally arrive at a portfolio of 9 eco-innovative projects with high value creation for the company.

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Life Cycle Assessment (LCA) is commonly used in companies as an environmental assessment tool. But it is also associated with a certain number of limitations, such as the lack or quality of the data collected. This problem is amplified when dealing with complex industrial systems, characterized by a large number of subsystems and components and an extremely long and uncertain life cycle. Different methods exist to precisely manage data uncertainty, but they are generally very time and resource consuming. When the objective of LCA is to guide the research of improvement projects, a high accuracy of the results is not necessarily necessary. We propose here a scenario-based LCA approach allowing to model with little information different possible operating trajectories of a complex industrial system. From the identification of particularly uncertain and relevant life cycle elements to be integrated (maintenance, spare parts, accidents, upgrading, life cycle modulation, end-of-life options), operating scenarios are built from an adapted tool, the SRI matrix (Stanford Research Institute). It can be used to quickly generate a set of four scenarios (worst case, best case, probable future and a different alternative) to understand the extent of possible environmental impacts depending on the operator's decisions and natural or political-economic hazards. The simulation of these scenarios allows to make the decisions taken on the basis of the LCA more reliable. The whole approach has been applied at Alstom Grid on AC/DC conversion stations for the primary aluminium industry.

Complex product development processes are evolving towards simulation driven design which leads to many heterogeneous computational models and design teams that interact with each other. However, this interaction creates a bottleneck for communication and models reuse throughout the design process because, very often, the model provider (i.e. analysts) and model users (i.e. designers) do not have the same level of understanding. In addition, the tools such as PDM (Product Data Management) or SDM (Simulation Data Management) consider the numerical models as black-box documents and they cannot access or link parameters and variables of models. The poverty of semantics in terms of simulation logics and design leads to a lack of interoperability between the contributing disciplinary simulation components, herein called numerical models. To reinforce this semantics, it is necessary to create a semantically-rich model characterization support to reduce knowledge gap between model provider and user, and to achieve a higher level of reuse. This work aims to introduce the first necessary step, herein, creation of domain ontology for formally characterizing reusable numerical model. Based on this common vocabulary, in automotive context, a Model Identity Card (MIC) is developed as an intermediate support which characterizes a model into five attributes. Physical Object, Interface, Methods, Means Usage, Validation and Verification. The MIC is illustrated with a Vehicle Thermic Comfort model example and a computer interface is developed to collect a series of representative MICs in a database.Copyright © 2013 by ASME.

So as to create innovative car silhouettes, we propose in this paper a model based on an Interactive Genetic Algorithm using an encoding of a design solution by a Fourier analysis approach. This model permits the designer to browse through generations of car profiles from an initial population of existing silhouettes. By qualitatively assessing each individual, the designer converge towards solutions complying with his/her requirements and preferences, possibly creating novelty and generating surprise. We describe here tests for assessing the efficiency of this innovative design platform. These tests are mainly based on a similarity index, a similarity measure being the perceived distance between two cars silhouettes. The results highlight a good convergence toward a satisfactory solution. In addition, this design process turns out to be very flexible because of the local and intuitive modifications allowed on a given individual solution at any moment of the design process.

Faced with the emergence of environmental problems resulting from human activities, ecodesign aims to offer a satisfactory response in the field of product and service design. However, when the products considered become complex industrial systems, characterized by a large number of components and subsystems, an extremely long and uncertain life cycle, or complex interactions with their geographical and industrial environment, an obvious lack of methodologies and tools is felt. This change of scale brings indeed different constraints both in the assessment of environmental impacts generated during the life cycle of the system (management and quality of data, level of detail of the study compared to the available resources...) and in the identification of appropriate responses (management of multidisciplinarity and available resources, training of actors, inclusion in a context of very upstream R&D...). This thesis aims to develop a methodology for the implementation of an eco-design approach for complex industrial systems. A general methodology is first proposed, based on a DMAIC process (Define, Measure, Analyse, Improve, Control). This methodology allows to define in a formalized way the framework of the approach (objectives, resources, perimeter, phasing...) and to rigorously accompany the ecodesign approach on the considered system. A first step of environmental assessment based on the Life Cycle Assessment (LCA) at a high systemic level is thus carried out. Given the complexity of the life cycle considered and the variability of operation of an industrial system from one site to another, a scenario-based approach is proposed in order to quickly grasp the possible extent of environmental impacts. The operating scenarios are defined using the SRI (Stranford Research Institute) matrix and include many elements rarely addressed in LCA, such as preventive and corrective maintenance, subsystem upgrades, and modulation of the system's life cycle according to the economic context. At the end of this LCA, the main impacting items of the system's life cycle are known and allow to undertake the second part of the eco-design approach focused on environmental improvement. A multidisciplinary working group is brought together during a creativity session centered around the eco-design strategy wheel (or Brezet wheel), an eco-innovation tool that requires few resources and little environmental expertise. The ideas generated in creativity are then processed through three successive filters, which allow: (1) to pre-select the best projects and to deepen them. (2) to build a portfolio of R&D projects using a multi-criteria approach that evaluates their environmental performance, but also their technical and economic performance and their value creation for customers. (3) to control the balance of the portfolio according to the company's strategy and the diversity of the projects considered (short/medium/long term aspects, systemic level considered...). All the work has been applied and validated at Alstom Grid on electrical conversion substations used in the primary aluminium industry. The deployment of the methodology has allowed to initiate a solid eco-design approach recognized by the company and to generate a portfolio of 9 eco-innovative R&D projects that will be implemented in the coming months.

The design of multi-physics systems involving engineers from different disciplines (mechanical, electronic, sensor physics, etc.), and especially systems intended to operate under severe conditions (under dimensional constraints, shock and vibration, withstanding high temperatures and high pressures), raises many difficult issues in the design of complex systems. These highly integrated products are characterized by multiple functional flows through common components. The high expectations of different engineers can over-stress the architectural modules, as well as the connections and performance of certain functions. This integration of multi-physics functions in size-limited products that operate under severe conditions results in an intense interaction between design parameters and expected functionality. As soon as one design parameter is changed, the performance of several functions can be affected. This is due to the high degree of performance optimization and the fact that several functions are part of the process flow resulting from a single component. In addition, some disciplines may be more constrained than others depending on the challenge of achieving the given performance and the concept under consideration. Hereafter, we refer to architectural modules, connections and disciplines as constrainable objects. Today, without any predictive tools to locate those aspects that are likely to be highly constrained, the consequences can be dramatic. For example, project management in the oil industry is often responsible for unacceptable deviations in project cost and schedule that can lead to project failure. In our study, we propose to semantically enrich conventional representations of product complexity. We use a DSM (Design Structure Matrix) to represent the physical connections in the design alternatives, a DMM (Domain Mapping Matrix) to link the functions with the architecture, and a QFD (Quality Function Deployment) matrix in an unconventional way, in order to propagate the engineers' vision of the components' performance as the traditional "voice of the customer". Our first contribution concerns the enrichment of these representations. We enrich the DSM representation with a physical connection typology, allowing a range of alternatives at a given design stage. For a connection, the information given on the nature of the likely difficulties is incorporated in a data model. We enrich the DMM representation by describing the functional flow through architectural modules. We adapt the QFD method to capture the voice of disciplines involved in the project. This ontological enrichment of design data makes it easier to manage conflicts in multi-physics system design. In this objective, seven dashboards are proposed to the design team as useful tools to converge from a set of potential architectural configurations to a single architecture. This convergence process is supported by the need to avoid too strong constraints on certain disciplines, this balance is achieved by the propagation of design constraints in the system. The seven dashboards are organized into two vectors: the ambition vector and the difficulty vector. The ambition vector indicates the degree of freedom in exploring the architecture design space. The difficulty vector provides heuristic information about the nature and levels of difficulty in achieving the performance goals. [.].

Today, the challenges brought by sustainable development require the development of new offers and new uses within the framework of an eco-innovation process integrating environmental and societal approaches.This thesis aims to study the interest of using creativity tools to instrument the idea generation and new concept generation phases during eco-innovation processes. This adaptation is argued on the conceptual level by showing the theoretical affiliations between the two tools and on the experimental level by presenting the results of our different experiments. We show that the EcoASIT tool has a strong potential in the eco-innovation process by proposing to efficiently stimulate the ideation phases on all the axes of sustainable development.From a state of the art on the concept of eco-innovation and on the eco-innovation support tools, we show that, if there are many tools, few of them are precisely focused on the idea generation phase, or ideation. To address this gap, our research is based on an adaptation of the creativity tool ASIT into EcoASIT.

Electronics in cars is becoming more and more complex and represents more than 30% of the overall cost of a car. For example, in a 2008 BMW 5 series, there can be up to 80 electronic computers communicating together and representing around 10 million lines of software code. Faced with this increasing complexity, automotive electronics manufacturers and suppliers are increasingly interested in efficient methods for developing, verifying and validating electronic modules. More precisely, they are focusing their efforts on the software part of these modules since it is at the origin of more than 80% of the problems detected on these products. In this context, we have conducted a research project whose objective is to propose a global approach to improve the quality of software embedded in vehicles. Our research starts with an audit of the processes and tools currently used in the automotive electronics industry. This audit allowed us to identify potential levers for improving software quality. Based on the results of the audit and taking into account the literature in the field of software quality, we have proposed a global approach to test case design for software products. Indeed, we have developed an automatic test generation platform for a software product. This platform consists in modeling the specifications of the software product to simulate it during tests, to focus on critical tests (having a high probability of detecting defects) and to drive the automatic generation of tests by quality criteria such as the coverage of the code and the specification but also the cost of the tests. The generation of critical tests is made possible by the definition of real use profiles per software product, as well as by the reuse of defects and tests capitalized on former projects. In addition to the algorithmic aspects of software testing, our approach takes into account organizational aspects such as knowledge and skills management and software project management. Our approach has been implemented on two real-life case studies of an automotive electronics supplier, with historical test data. The results of our experiments reveal significant quality gains: more defects are found earlier and in less time.

In this thesis, we propose a methodological framework for the preliminary design phase in the automotive industry, in order to manage the trade-off between, on the one hand, the architectural constraints to which a mechanical subsystem is subjected, and on the other hand, a satisfactory contribution of the subsystem to the minimization of noise in the vehicle interior. The proposed methodology allows us to engage in negotiations between automotive architects and mechanical engineers on the compliance or non-compliance of architectural constraints of a subsystem or a component, as well as on the achievement of the targets of the specifications regarding the vibro-acoustic performances. The proposed methodological framework consists of five steps: 1, modeling of the design problem, including (a) modeling of the vibro-acoustic performances and (b) modeling of the architecture constraints. 2, the metamodeling (mathematical approximation) of the resulting design problem using kriging metamodels. 3, the formulation of the design problem as a multi-objective optimization problem. 4, the generation of this multi-objective optimization problem using the Pareto boundary metamodel and the normalized constraints method. 5, a negotiation step between the architecture constraints and the performance of the mechanical subsystem. To handle the problem of archtecture constraints, in the preliminary design phase, we introduce a method to express, by a so-called architecture criterion, the compliance or non-compliance with ge��ometric constraints. The originality of this method consists in the fact of migrating the step of allocating envelope volumes under a CAD system to a CAE system that is more accessible to engineers since it is in this system that they manage their finite element models. We also introduce a method for aggregating the vibro-acoustic performance of a mechanical subsystem into a single real-valued criterion (indicator). This technique allows an efficient reduction of the important dimension of a design problem related to the study of a mechanical subsystem with multiple vibro-acoustic performances. The application of the methodology to a case study, in the automotive domain, allowed to demonstrate its efficiency to significantly improve the vibro-acoustic performances of a body-in-white (bare body of an automobile) while respecting tight architectural constraints due to an envelope volume allocated to the vehicle powertrain. Finally, with this methodological framework, negotiations between architects and engineers are no longer based on qualitative judgments, but are now based on quantitative criteria for both architectural constraints and mechanical performance.

Faced with the health crises that have shaken the agri-food sector in recent years, such as mad cow disease, the legislative and normative requirements in terms of food safety are becoming more and more draconian. For example, the EC 178/2002 regulation stipulates that each company must have the means to ensure the traceability of the foodstuffs it puts on the market. It is in this context that we conducted a research-action whose ambition is to contribute to establish methodological and conceptual bases to address the issue of traceability of food products. Our approach starts with a functional analysis of the need to identify the beneficiaries of a traceability system (noted ST), to characterize its service functions and to propose quantifiable criteria to assess its performance. After this functional phase, we move on to a technical phase consisting of defining and characterizing the technical functions performed by the TS in order to meet the expectations of its beneficiaries. Examples of solutions and measurable assessment criteria are associated to each function. Then, we propose a generic data model describing the nature and structure of the information that the ST must be able to manage. On these bases, we have developed a computer platform composed of a set of modules intended for the restitution of traceability data and the management of the ST.

This thesis work focuses on the control and integration of costs in aeronautical design projects. The study of Design to Cost practices (name of the cost control method used in some companies) at Airbus and Eurocopter (two aeronautical companies of the EADS group) allows us to identify three classes of dysfunctions related to cost control in the design projects of these two companies: dysfunctions related to the Design to Cost business, those related to the project context and those related to the actors. We propose to solve some dysfunctions related to the Design to Cost business by integrating knowledge management in the design cost control process. The methods and tools related to cost control methods can be classified into three main processes: target management, management of cost reduction opportunities and monitoring / steering. We experiment the proposed Design to Cost process on the management of cost reduction opportunities. For this we propose three tools. The first one is a typology of changes that allows to characterize each cost reduction opportunity according to the changes it induces. The second is a list of cost drivers that helps to identify the parameters whose modification significantly influences the costs. Finally, the third is a model whose implementation aims to exploit past opportunities: OSIRIS (Optimiser for Saving Idea Reuse). The contributions have been validated via a computer prototype tested by the members of the Design to Cost Airbus team.

When making a decision, the decision-maker in a company is generally faced with the following situation: he or she has a set of alternatives, which are combinations of action variables, and is asked to achieve a certain number of objectives, which are characterized by a more or less large number of performance indicators. These objectives cover all of the company's relationships with the various parties that benefit from the results of its activities and with whom it interacts. The purpose of the performance indicators is to measure the company's success in meeting the expectations and needs of these parties: customers, shareholders, employees, the community. . And to its own expectations. The decision-maker needs to evaluate each of the alternatives according to each of the choice criteria selected and which represent the objectives to be achieved, and to evaluate each of these alternatives globally according to all the criteria. This work is placed in the context of high-level managerial decision support where the actions are potential projects for the development of the company's activities. The proposed approach, called SimulValor, uses system dynamics to model and simulate action alternatives and to evaluate their performances. In summary, the SimulValor approach aims at evaluating different action alternatives concerning the configuration of the company's activities by simulating the value flows that link the actions to the performances and the performances to the values generated to the beneficiaries. The main difficulty of the method is the extraction, harmonization and quantification of the qualitative data that characterize the influence links (and especially the utility functions) existing between the modeled elements.

This work deals with the methodological problems in the projects of implementation of Technical Information Systems (TIS) in companies. Its field of application is production engineering. The objective is to improve two aspects of these problems: the specifications of the project owner and the project manager, and the global approach of these projects. To do this, we propose a domain repository, developed using standard specification diagrams. Oriented towards the expression of TDM needs, the repository can be reused in future ITS developments during the domain analysis phase. The repository development process is streamlined. It is intended to be a methodological guide for the TIS engineering itself. It involves the main actors following an iterative process. This approach is also contextual in order to better understand the singularities of the projects and sufficiently flexible to respect the creative character of the engineering professions.

Our work concerns the design of products in the preliminary phases, or pre-design of products, found in the literature under the expression of conceptual design, at the crossroads between the fields of Artificial Intelligence applied to design, integrated and simultaneous design, design theories and industrial methodologies such as Value Analysis. In a first step, we proposed enriched models of specifications. These are functional models of objectives and satisfactions (or preferences) related to a product, its associated services and its design-industrialization project, trying to take into account the following aspects: uncertainty, context, multi-actors and evolution. In a second step, we worked on the way to translate these product objectives into solution concepts (or architectures) in the most automated way possible: by synthesis methods, or by semi-automatic methods which, far from taking the place of the designers, allow them on the contrary to have generic design tools giving them the means to devote themselves to creativity tasks. In particular, we have contributed to the development of a method for concept synthesis in spatial allocation (constraint programming technique) and methods for concept synthesis of planar mechanisms (neural network, multi-agent, case-based design techniques). In a third step, when concepts have been proposed, their performance must be evaluated, the difficulty residing on the one hand in the coarse definition of a concept and thus in their ability to represent entire classes of solution products, and on the other hand in the absence of detailed design. Reasoning from incompletely defined models is an important part of our work. Methods from qualitative physics have been developed, and performance modeling has been approached in a probabilistic and fuzzy way as well as in an approximated way by metamodeling techniques. Finally, we have addressed the measurement of the adequacy of the performances of a concept with the specifications, for a generic product, in order to develop functionalities of performances, costs and risks monitoring in the pre-design phase, as well as functionalities of help to the re-design and optimization of the concepts (methods based on qualitative physics or on a Monte-Carlo type simulation).

In project management, weighting procedures are associated with the evaluation of parameters involved in the decision-making process. In spite of this issue, field tools are very often not adapted to project requirements. Some even lead to inaccurate results. At the same time, the solutions available in the research world are not always flexible enough to be used immediately in the field. This thesis provides some answers both on a theoretical and practical level. It is part of the more specific framework of so-called cross-sorting tools. This designation includes any method reducing the problem to a set of binary comparisons of the elements to be weighted in order to simplify the task of the decision group. Our contributions consist first of all in a greater flexibility in taking into account the opinions of the decision makers. A general mathematical formulation of the problem is proposed as well as perspectives, based on fuzzy logic, for a better management of the imprecision inherent in the judgment. Our contribution also concerns the detection and treatment of the inconsistency induced by the aggregation of binary comparisons which often contain redundant information without necessarily being concordant. An original coherence indicator is proposed as well as an iterative procedure to improve this coherence. Moreover, the introduction of the notion of voting entity allows to consider a larger variety of voting strategies and to target the assistance brought to the decision group. Finally, on a practical level, an original concept of asynchronous and distributed cross sorting platform is proposed. It offers great flexibility in the design and implementation of a cross sorting procedure in a project. A computer model has been developed in order to validate a part of its functionalities.

We present in this thesis the Qdes (qualitative design) method of functional design of a dynamic system in the fields of hydromechanics, electronics, automation, chemistry, biology. . This method is applied from the pre-design phase, whereas a design alternative proposed by the designer is only defined by its schematic diagram, making it possible to invalidate as soon as possible entire families of real differential systems. This method is inspired by the work done in qualitative physics. It consists in carrying out a qualitative simulation analysis of the total supply type, and then to judge the degree of adequacy of the result obtained (supply graph between qualitative states) with functional dynamic specifications in terms of the intersection of two graphs. The first point of this work consists in fundamentally revisiting the total provisioning method with the non-causal resolution technique of constraint propagation. A new simulation algorithm is proposed which includes a formal qualitative derivation, a new state enumeration principle which avoids the problem of qualitative chaos, an explicit sorting of states into instants or time intervals which alternate during the determination of transitions. The second part of this thesis proposes a design model based on an original definition of a functional dynamic specification (set of qualitative curves for some variables, which can have approximate values and relative temporal dependencies). New algorithms for intersecting a set of specifications with a supply graph and for managing symbolic times are proposed. Qdes manages a design history in the form of a hierarchy of result graphs allowing to reason at different problem grain sizes (filter and aggregation operators). A design methodology is proposed, a class of specific problems is identified and a comparison is made with other design systems.