THOMAS Andre

The emergence of Cyber Physical System has dramatically impacted the use of traditionally centralized control system in responding to unexpected events. Rush order is quite common unexpected event in the current dynamic market characteristics and has significant perturbing ability to a centrally predictive schedule. This paper is aimed to propose a Consensus algorithm for Multi-agent based Manufacturing system (CoMM) to control the rush order and henceforth minimize a makespan. Consensus is an algorithmic procedure applied in control theory which allows convergence of state between locally autonomous agents collaborating for their common goal. Leader-Follower communication approach was used among the multi-agent to deal with the perturbing event. Each agent decides when to broadcast its state to neighbor agents and the controlling decision depends on the behavior of this state. The consensus algorithm is initially modeled by networking all contributing agents. After this, it is validated with simulation experiment based on academic full-sized application platform called TRACILOGIS platform. The results showed that the consensus algorithm has significantly minimized the impact of rush order on makespan of manufacturing orders launched on a system.

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This editorial introduces the special issue in the Elsevier journal Computers in Industry that analyses how the digital transformation of manufacturing is speeded up by two important drivers: cloud services and resource virtualization, which are vital for implementing the main building blocks - Cyber Physical Production Systems and Industrial Internet of Things - in the “Industry of the future” framework. The context of this special issue is firstly presented, with a specific focus on the federative concept of Industry 4.0. A framework characterizing research activities led in the field of the digital transformation of manufacturing processes and systems is then introduced. This framework is used to present and position the 12 papers composing the special issue. Perspectives are finally introduced as a guideline for future work in the digital transformation of manufacturing through cloud services and resource virtualization.

In wireless sensor networks, the aim of storage protocols is to efficiently replicate data across nodes and to improvedata collection and querying by sinks. Among them, in-network storage protocols replicate data in a set of nodes thatdepends on some characteristics such as network topology and geographic location. Researchers have proposed varioustechniques to implement in-network storage. In this article, we summarize and highlight the key ideas of existing proto-cols which are further classified into three categories (reactive, unstructured proactive, and structured proactive) basedon topology, load balancing, transmission strategy, and reliability. Benefits and drawbacks of each protocol are studiedand compared with different requirements. Finally, future research directions are provided for efficient in-network stor-age in wireless sensor network.

In order to ensure a reliable building life cycle management, it is essential to generate an accurate and up-to-date referential mock-up that will be used for renovation, extension and maintenance. Based on this statement, we carried out, in a previous work, a research study in the sake of reconstructing a 3D CAD model from a point cloud acquired using a Lidar. This point cloud is processed automatically to detect planes and contours and to generate the 3D CAD model. However, during the life cycle of the project, different actors from different fields intervene on the building, which creates several communication conflicts, and this means a loss of time, energy and money. In order to ensure a constructive collaboration and a simplified data exchange between the different contributors in the building, we continued our work to propose, in this paper, an automatic conversion of a point cloud to a 3D BIM file. This conversion induces the passage to the standard IFC format and the integration of a valuable knowledge in it. To do so, an automatic classification of contours into architectural elements is proposed. It consists in defining a hierarchical classification rule reproducing the human reasoning for classifying the architectural elements. Then, based on the classified set of polygons, an automatic generation of 3D IFC model is proposed.

This book gathers the peer-reviewed papers presented at the seventh edition of the international workshop "Service Orientation in Holonic and Multi-Agent Manufacturing - SOHOMA'17", held on October 19-20, 2017 and organized by the University of Nantes, France in collaboration with the CIMR Research Centre in Computer Integrated Manufacturing and Robotics at the University Politehnica of Bucharest, Romania, the LAMIH Laboratory of Industrial and Human Automation Control, Mechanical Engineering and Computer Science at the University of Valenciennes and Hainaut-Cambrésis, France and the CRAN Research Centre for Automatic Control, Nancy at the University of Lorraine, France. The main objective of SOHOMA'17 was to foster innovation in smart and sustainable manufacturing and logistics systems and in this context to promote concepts, methods and solutions addressing trends in service orientation of agent-based control technologies with distributed intelligence. The book is organized in eight parts, each with a number of chapters describing research in current domains of the digital transformation in manufacturing and trends in future service and computing oriented manufacturing control: Part 1: Advanced Manufacturing Control, Part 2: Big Data Management, Part 3: Cyber-Physical Production Systems, Part 4: Cloud- and Cyber-Physical Systems for Smart and Sustainable Manufacturing, Part 5: Simulation for Physical Internet and Intelligent & Sustainable Logistics Systems, Part 6: Formal Methods and Advanced Scheduling for Future Industrial Systems, Part 7: Applications and Demonstrators, Part 8: Production and Logistic Control Systems. The contributions focus on how the digital transformation, such as the one advocated by "Industry 4.0" or "Industry of the future" concepts, can improve the maintainability and the sustainability of manufacturing processes, products, and logistics. Digital transformation relates to the interaction between the physical and informational worlds and is realized by virtualization of products, processes and resources managed as services.

The need of building process industrialization has seed up the use of new Information Technologies to enhance the productivity and quality of building projects. In particular, the use of the Building Information Modeling (BIM) assets and real time follow-up based on the Cyber Physical System paradigm could be a source of valuable data to support planning and monitoring activities throughout the building life cycle. In the context of process industrialization one challenging issue is the transformation of design data into manufacturing data. The main contribution of this paper is the automatic transformation from engineering bills of material (e-BOM) to manufacturing (m-BOM) ones based on routing sheets and resources’ availability status. Illustrated by an actual prefabricated building case study, a methodological approach to dynamically adapt the e-BOM to m-BOM supported by a generic BOM and its implementation architecture are proposed.

Commercial aircrafts use black-box required for crash investigation purposes. While a black-box can be easily recovered in crash events on land, the same does not apply to crash events in great deep ocean water. This paper presents a new solution towards solving black-box data loss on ocean crash using a paradigm called communicating materials. The solution is developed through uniformly integrating hundreds of micro sensors nodes in the aircraft structure. The nodes could then construct a Wireless Sensor Network (WSN) inside the aircraft. When a crash is detected by the aircraft system, the black-box data could be stored in all nodes using data storage protocols for WSN. Since nodes are uniformly deployed in the whole aircraft structure, investigators could thus gather preliminary crash causes information from the nodes inside any floated aircraft wreckage in the ocean. This solution was evaluated using Castalia simulator in terms of reliability, storage capacity, and energy efficiency.

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Nowadays complex control systems are rising and especially hybrid control architectures which are developed to face the manufacturing control challenges that occur with the last industrial revolution and the emerging of industry 4.0. This work presents an application, on a testing platform, of a scheduling algorithm, with multi-criteria objectives, developed for Acta-Mobilier company suffering from high rework rate. This algorithm will inscribe itself in a hybrid control system based on smart entities. The main objective is to validate the contribution of the proposed algorithm in a disturbed environment. The platform, implemented with a multi-agent's system, allows to measure the reliability of the proposed algorithm used on a complex system in the particular case of high rework rate.

In order to deploy AGVs in industry, it is mandatory to consider the tradeoff between smartness and embeddability. This paper aims at making the manufacturing research community more sensitive about this tradeoff and its consequences. Nowadays, AGVs are widely chosen by manufacturers to implement flexible material-handling systems which are necessary to cover the industrial requirements. However, many issues, presented in this paper, must be tackled to deploy these AGVs. A tradeoff-oriented procedure is proposed by considering these issues in flexible manufacturing system applications. Then, an approach is proposed to illustrate this procedure by providing simulation and experimental results. This approach is also used to roughly describe the smartness/embeddability tradeoff.

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Development of future industry has become an active research area in the recent years. A structured national workgroup, called IMS², has emerged in France over the last decade. The aim of this paper is, regarding four highlighted general research topics (namely agility, new technologies, sustainability and industrial dissemination), to synthetize the general research works on intelligent manufacturing and to demonstrate the principal contributions developed within the framework of this national workgroup. After a critical evaluation of the proposed approaches towards alternative solutions, this paper suggests a 2030 roadmap for the workgroup.

Years ago, advances in electronics led to electronic components such as RFID, capable to identify a product via a unique identification number. This capacity gave rise to PLIM systems (Product LifeCycle Information Systems), which are information systems ensuring the retrieval of product information wherever and whenever during the product’s lifecycle. However, this article shows that such systems are not yet prepared to treat massive data, generated by IoT infrastructure. To solve this issue, situation awareness is a possible answer. In this paper, this notion is detailed and presented via different examples taken from the literature. Yet, the needed tools to support situation awareness in PLIM systems are still lacking, because there are still some scientific and technical challenges to solve. These challenges are detailed in this paper as well.

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Nowadays complex control systems are rising and especially hybrid control architectures which are developed to face the manufacturing control challenges that occur with the last industrial revolution and the emerging of industry 4.0. This work presents an application, on a testing platform, of a scheduling algorithm, with multi-criteria objectives, developed for Acta-Mobilier company suffering from high rework rate. This algorithm will inscribe itself in a hybrid control system based on smart entities. The main objective is to validate the contribution of the proposed algorithm in a disturbed environment. The platform, implemented with a multi-agent's system, allows to measure the reliability of the proposed algorithm used on a complex system in the particular case of high rework rate.

This volume gathers the peer reviewed papers which were presented at the sixth edition of the International Workshop “Service Orientation in Holonic and Multi-agent Manufacturing—SOHOMA’16” organized on October 6–7, 2016 by the New University of Lisbon, Portugal in collaboration with the CIMR Research Centre in Computer Integrated Manufacturing and Robotics of the University Politehnica of Bucharest, Romania, the LAMIH Laboratory of Industrial and Human Automation Control, Mechanical Engineering and Computer Science of the University of Valenciennes and Hainaut-Cambrésis, France and the CRAN Research Centre for Automatic Control, Nancy of the University of Lorraine, France.info:eu-repo/semantics/publishedVersio.

This paper presents an application of the measurements-based AHP to define a two-stage algorithm for product-driven systems control, in case of an unexpected event. This algorithm is made of two stages: the first one aims to define which kind of strategy the product should adopt (wait ̧ react by it self or switch back to centralized mode) while the second one helps to choose the most appropriate resource able to fulfill the product requirements. The methodology is detailed on a simple case study.

No summary available.

Commercial aircrafts use black box comprising a Flight Data Recorder (FDR) required for crash investigation purposes. While FDR can be easily recovered in crash events on land, the same does not apply to crash events in great deep ocean water. This paper presents a new solution towards solving FDR data recovery using a paradigm called "communicating materials". The solution is developed through uniformly integrating hundreds of tiny sensor nodes in the aircraft structure. The nodes could then construct a Wireless Sensor Network (WSN) inside the aircraft. Thus, the latest FDR data could be stored in the nodes using data storage protocol for WSN. The proposed storage protocol uses the probabilistic-based flooding scheme to forward data to all nodes inside the aircraft structure within the lowest delay. To improve reliability and collision-avoidance of flooding, different complementing corrective measures are used based on neighborhood information. The protocol is evaluated using Castalia/OMNeT++ simulator.

A new area is coming with communicating materials able to provide diverse functionalities to users all along the product lifecycle, during the design, manufacturing, use and dismantling phases. These materials can track their own evolution all along the product lifetime, gather helpful information and thus allow information continuum at all time and everywhere. Usually, these functionalities are fulfilled via the integration of specific electronic components into the material (wireless sensors nodes, RFID tags). The present paper forms part of this framework in considering that thousands of micro-sensor nodes are integrated into a precast concrete. Data management in the integrated sensor nodes requires Wireless Sensor Network (WSN) protocols development. We recently developed a data storage protocol, called USEE, for communicating materials. To extract this information, we recently developed also a data retrieval protocol, called RaWPG. In this paper, the performances of these protocols are evaluated on the case study of the precast concrete lifecycle management.

In order to deploy AGVs in industry, it is mandatory to consider the tradeoff between the smartness and the embeddability. This paper aims to make the manufacturing research community more sensitive about this tradeoff and its consequences. Nowadays, AGVs are widely chosen by manufacturers to implement flexible material-handling systems which are necessary to cover the industrial requirements. However, many issues, presented in this paper, must be tackled to deploy these AGVs. A tradeoff-oriented procedure is proposed by considering these issues in flexible manufacturing system applications. Then, an approach is proposed to illustrate this procedure by providing simulation and experimental results. This approach is also used to roughly describe the smartness/embeddability tradeoff.

Commercial aircrafts use black-box required for crash investigation purposes. While black-box can be easily recovered in crash events on land, the same does not apply to crash events in great deep ocean water. This paper presents a new solution towards solving black-box data loss on ocean crash using a paradigm called communicating materials. The solution is developed through uniformly integrating hundreds of micro sensors nodes in the aircraft structure. The nodes could then construct a Wireless Sensor Network (WSN) inside the aircraft. When a crash is detected by the aircraft system, the black-box data could be stored in all nodes using data storage protocol for WSN. Since nodes are uniformly deployed in the whole aircraft structure, investigators could thus gather preliminary crash causes information from the nodes inside any floated aircraft wreckage in the ocean. This solution was evaluated using Castalia simulator in terms of reliability, storage capacity, and energy efficiency.

In order to ensure an overall efficient production performance , the industrial experiences and research activities have demonstrated the interest of hybrid control systems, which couple a predictive scheduling with a distributed reactive control. In this context , it is commonly accepted that using the multi-agent systems (MAS) paradigm enhances the reactivity to treat disturbances and improves the decision making process of a shop floor. Each agent could have different capability (evolution, learning etc.) and the whole system, based on the agent interaction, leads emerging behaviors to dynamically adapt the production schedule. This paper is aimed to develop and simulate a negotiation scenario to deal with disturbed manufacturing processes. The scenario was implemented on the basis of TRACILOGIS test-bed platform. The negotiation protocol consists in setting the best sequential priority based on some performance indicators. This protocol is compared with a purely reactive production mode.

A new area is coming with communicating materials which is able to provide diverse functionalities to users all along the product lifecycle. These materials can track their own evolution all along the product lifetime, gather helpful information and thus allow information continuum at all time and everywhere. These functionalities are fulfilled via the integration of thousands of specific electronic components into the product’s material. The present paper forms part of this framework in considering that thousands of micro-sensor nodes are integrated into the material. Specific Wireless Sensor Network (WSN) storage protocols were recently proposed for communicating materials, that uniformly replicate information in the integrated nodes. To extract this information during the product lifecycle, a dedicated WSN data retrieval protocol called RaWPG is presented in this paper. Unlike well-known literature protocols, RaWPG avoids request flooding because all data are uniformly replicated in WSN. With usual protocols, this may lead to high response duplication rate. RaWPG employs three mechanisms. First, the random walk is used as multi-hop process to forward the request to further nodes. Then, the pull gossip mechanism is added to interrogate the neighbor nodes during each hop. Finally, a mechanism called farthest neighbor selection is added. Only the farthest and most powerful neighbor is selected as next hop for improving the transmission reliability of request and response messages. The performances of the proposed protocol are evaluated based on a case study, and compared to results obtained with classic approaches issued from the literature.

A communicating object, or connected object, is a key element of the Internet of Things to shift a perceptible real world into a wide digital virtual world known as the cyber-physical system. Knowing that sustainability, safety, and logistic issues are among the significant goals and challenges of modern industrial enterprises, the communicating object can be a rele- vant concept to guarantee safety performance in logistics and warehouse management. This article presents the impacts and advantages of the communicating object in smart logistics and the design of a communicating object model inspired from Internet of Things European research projects, which controls and monitors safety risks in a hazardous and chemi- cal industrial context. Generic safety-based scenarios are presented, which rely on a set of negotiated interaction mechanisms for storage and picking. The relevant deployment of intelligence in a warehouse management system leads to propose a new concept called ‘‘IoT-controlled Safe Area.’’ Our contribution is to bring informational, communica- tional, and decisional capabilities close to the warehousing physical world thanks to the communicating object. This enables achieving safety assurance with a decrease in the decision-making delay and an increase in the solving efficiency of local and dynamic disruptions, while avoiding inherent shortcomings of the warehouse management system centraliza- tion. For this, an industrial implementation is presented.

A new Internet of Things area is coming with communicating materials, which are able to provide diverse functionalities to users all along the product lifecycle. As example, it can track its own evolution which leads to gather helpful information. This new paradigm is fulfilled via the integration of specific electronic components into the product material. In this work, ultra-small Wireless Sensor Networks (WSN) are used for large scale materials such as concrete in smart building. Indeed, storage of lifecycle information and data dissemination in communicating materials are very important issues. Therefore, this paper provides solution for storing data by systematic dissemination through the integrated WSN. It presents USEE, an uniform data storage protocol for large scale communicating material. USEE guarantees that information could be retrieved in each piece of the material by intelligently managing data replication among each neighborhood of the WSN. Unlike related protocols of the literature, USEE considers in the same set uniformity storage in the whole network, the data importance level, and the resource constraints of sensor nodes. When compared with related protocols such as RaWMS, DEEP, and Supple, USEE shows an uniform dissemination and low communication overhead tradeoff for all the data importance levels.

Intelligent products carrying their own information are more and more present nowadays. A lot of research works focuses on the usage of such products during the manufacturing or delivery phases. This led to important contributions concerning product data management in the framework of HMS (Holonic Manufacturing Systems). This paper aim is to: (1) make a review of the major contributions made for EOL information management (data models, communications protocols, materials, …) in the framework of a circular economy, (2) have a first overview on the industrial reasons explaining why these systems are not widely implemented. This previous points help to highlight potential research directions to develop in the near future.

The rapid development of Internet of Things has triggered the multiplication of communication nodes based on Radio-Frequency Identification (RFID) and Wireless Sensor Networks (WSNs) in various domains such as building, city, industry, and transport. These communication nodes are attached to a thing or directly included in the material of the thing to form a communicating material. In communicating material, one of the desired objectives is to merge the logical data with its physical material, thus simplifying the monitoring of its life cycle, the maintenance operations, and the recycling process. In this context, the initial form of the communicating material can evolve during its lifecycle. It can be split, aggregated with other materials, or partially damaged. However, the entire information in the material should always be accessible after each change. Thus, the objective of this research is to develop specific algorithms for efficient dissemination of information in the material in order to limit information losses. Two dissemination algorithms hop-counter-based and probabilistic-based are proposed for storing data by using WSNs, and non-localized and localized storage is considered. Non-localized storage ensures that information can be retrieved from each piece of the material by using a uniform data replication process. Localized storage ensures that the information is stored in a limited region of the material. Castalia/OMNeT++ simulator is used to compare the performance of the proposed algorithms with other similar protocols such as DEEP, Supple, and RaWMS.

A new area is coming with intelligent materials able to provide diverse functionalities to users all along the product lifecycle, during the design, manufacturing, use and dismantling phases. These materials can track their own evolution all along the product lifetime, gather helpful information and thus allow information continuum at all time and everywhere. Usually, these functionalities are fulfilled via the integration of specific electronic components into the material (wireless sensors nodes, RFID tags). The present paper forms part of this framework in considering that thousands of micro-sensor nodes are integrated into a concrete precast. All nodes store different information of precast properties in their memory requiring designing a specific Wireless Sensor Network (WSN) protocol to extract this information. The proposed protocol employs three mechanisms. First, the random walk is used as multi-hop process to forward the request to further nodes. Then, the pull gossip mechanism is added to interrogate the neighbor nodes in each hop. Finally, a mechanism called farthest neighbors selection is added. Only the farthest and most powerful neighbor is selected as next hop for improving the reliability of the original random walk process.

This paper presents an application of measurements-based AHP to define a two-stage algorithm for product-driven systems control, in case of un-expected event. This algorithm is made of two stages: the first one aims to de-fine which kind of strategy the product should adopt (wait¸ react by it self or switch back to centralized mode) while the second one helps to choose the most appropriate resource able to fulfill the product requirements. The methodology is detailed on a simple case study.

The impacts of using different order promising policies in traditional manufacturing industries are usually well known and documented in the literature. However, for industries facing divergent processes with co-production (i.e. several products simultaneously produced from a common raw material) as in the sawmilling industry, the evaluation, comparison, and selection of policies is not a trivial task. In this paper we compare different sawmilling industry order promising policies for various market conditions and demonstrate how and when these characteristics may call for Available-To-Promise (ATP), Capable-To-Promise (CTP), or other policies. It has been demonstrated that the best policy often differs from what would have been optimal in a classical manufacturing context (e.g. assembly).

A new area is coming with intelligent materials able to provide diverse functionalities to users all along the product lifecycle, during the design, manufacturing, use and dismantling phases. These materials can track their own evolution all along the product lifetime, gather helpful information and thus allow information continuum at all time and everywhere. Usually, these functionalities are fulfilled via the integration of specific electronic components into the material (wireless sensors nodes, RFID tags). The present paper forms part of this framework in considering that thousands of micro-sensor nodes are integrated into a concrete precast. All nodes store different information of precast properties in their memory requiring designing a specific Wireless Sensor Network (WSN) protocol to extract this information. The proposed protocol employs three mechanisms. First, the random walk is used as multi-hop process to forward the request to further nodes. Then, the pull gossip mechanism is added to interrogate the neighbor nodes in each hop. Finally, a mechanism called farthest neighbors selection is added. Only the farthest and most powerful neighbor is selected as next hop for improving the reliability of the original random walk process.

This thesis is a contribution to the modeling, planning and optimization of transport for the supply of forest wood to primary processing industries. In this field, the climatic hazards (grounding of wood by storms), sanitary hazards (bacteriological and fungal attacks on wood) and commercial hazards (variability and increasing demand of the markets) push the various actors of the sector (forestry contractors and operators, transporters) to review the organization of the logistic supply chain, in order to improve the quality of service (adequacy of supply-demand) and to decrease the costs.The main objective of this thesis was to propose a steering model to improve the performance of forest transport, while respecting the constraints and practices of the sector.The results establish a hierarchical planning approach for transport activities at two decision levels, tactical and operational. At the tactical level, a multi-period optimization allows to respond to orders by minimizing the global transport activity, under the constraint of the aggregate capacity of the accessible means of transport. This level allows the implementation of load smoothing policies and the organization of subcontracting or partnerships between transport actors. At the operational level, the tactical plans allocated to each carrier are disaggregated, to allow an optimization of the fleets' routes, under the constraint of the physical capacities of these fleets. The optimization models of each level are formalized in mixed linear programming with binary variables. The applicability of the models was tested using an industrial dataset in the Aquitaine region and showed significant improvements in the exploitation of transport capacities compared to current practices.The decision models were designed to adapt to any organizational context, whether partnership or not: the production of the tactical plan has a generic character without presumption of the organization, this one being taken into account, in a second time, at the level of the operational optimization of the transport plan of each actor.

The objective of this thesis is to propose a tool for the production planning of a supplier and to study the means to improve the coordination between this supplier and the customer plants. Applied to the automotive industry, this thesis is based on the case of mechanical factories (engine, gearbox, and ground connection parts factories) that supply vehicle assembly plants.By analyzing the demand of customer factories, we highlight the factors of variability of this demand and propose ways to improve coordination with the supplier through a more efficient sharing of information. For the supplier's production planning, we propose a mathematical model in the form of a linear integer program. This model allows to define a detailed production plan by respecting the existing constraints and by aiming at four objectives: to satisfy the forecasted demand, to reach the safety stocks, to balance the stocks between the products, and to smooth the production. The interest brought by this model is demonstrated by tests performed on real data. Knowing that the proposed model is intended to be used in the framework of a rolling horizon planning, we analyze by simulation the influence of two parameters: the planning frequency and the length of the frozen horizon. We give recommendations on the choice of these parameters in order to ensure a good compromise between the service rate, the stock level, and the stability of the planning. Finally, to improve the coordination between the client factories and the supplier, we study two avenues in particular: the improvement of the reliability of the forecasts communicated to the supplier and the extension of the time allowed to the supplier to satisfy the demand. The interest of implementing these proposals is evaluated by simulation.

Of interest are recent advances and on-going research in holonic and agent-based systems for manufacturing. Industrials are seeking for models and solutions that are not only able to provide efficient overall production performance, but also to face reactively a growing set of unpredicted events. One important research activity in the field focuses on holonic/multi-agent control systems that integrate predictive/proactive and reactive mechanisms into agents/holons. The demand for large scale systems running in complex and even chaotic environments requires the consideration of new paradigms and technologies that provide flexibility, robustness, agility and responsiveness. Holonic systems are, actually by definition, targeting challenges that include coping with the heterogeneous nature of manufacturing systems and their on-line interactive nature in combination with competitive pressures. Multi-agent systems is a suitable approach to address these challenge by offering an alternative way to design control systems, based on the decentralization of control functions over distributed autonomous and cooperative entities. Also, the concepts of Intelligent Product (or active product) and related techniques for product-driven automation are of interest.

This editorial introduces the special issue on Emerging Information and Communication Technology (ICT) concepts for smart, safe and sustainable industrial systems in the Elsevier journal Computers in Industry. The 13 papers in this special issue were selected because of their high quality and also because they propose emerging ICT solutions that address at least one of the three dimensions we suggest are basic requirements to design usable future Industrial Systems that must be safe, smart and sustainable. Previous global discussions about the state of the art with regard to the topic of this special issue are provided, as well as exploratory guidelines for future research in this area.

The impacts of using different order acceptance policiesin manufacturing sectors are usually well known and documented in the literature. However, for industries facing divergentprocesses with co-production (i.e. several products produced at the same time from a common raw material),the evaluation, comparison, and selection of policiesare not trivial tasks. This paperproposesa framework to enable this evaluation. Using a simulation model that integrates a custom-builtERP, we compare and evaluate different order acceptance policiesin various market conditions. Experiments are carried outusing a case from the forestproducts industry. Results illustrate how and when different market conditions related to divergent/co-production industries may call for Available-To-Promise (ATP), Capable-To-Promise (CTP),and other known strategies. Especially, we show that advanced order acceptance policies like CTP may generate a better income for certain types of market and, conversely to typical manufacturing industries, ATP performs better than other strategies for a specific demand patterns.

Raw material heterogeneity, complex transformation processes, and divergent product flowsmake sawmilling operationsdifficult to manage. Most north-American lumber sawmillsapply a make-to-stock production strategy, some accepting/refusing orders according to available-to-promise (ATP) quantities, while a few uses more advanced approaches. This article introduces a simulation framework allowing comparing and evaluatingdifferentproduction planning strategies as well as order management strategies. A basic ERP system is also integrated into the framework (inventory management, lumber production planning algorithms, ATP and CTP calculation, etc). The user can configure the production planning and order management process, and evaluate how they will perform in various market contexts using the discrete event simulation model.

With traditional PLM (Product Lifecycle Management), people think towards the future: first comes product development, then manufacturing, then support and finally disposal -- data flows only in forward direction. With the CL2M (Closed-Loop Lifecycle Management) concept, there are also flows going backwards, enabling better visibility and control of the product throughout its PLC (Product Life Cycle). CL2M uses "intelligent products" to gather information at any instant of the PLC and to make it available on downstream or upstream PLC phases. However, information is often deported on a database and is accessed remotely via a network pointer carried by the product. To bring the CL2M concept a step further, this paper addresses a dual challenge: i) providing a new kind of intelligent material capable of undergoing physical transformations without losing its communication ability and the data that is stored on it, ii) providing a framework to achieve a high degree of data synchronization (i.e. enabling data updates on the product, regardless of the network availability). An applicative scenario is presented, showing how this kind of material is put into practice in the context of "communicating medical garments" and how the requirements of the desired degree of data synchronization can be reached.

Nowadays, industrials are seeking for models and methods that are not only able to provide efficient overall production performance, but also reac-tive facing a growing set of unpredicted events. One important research activity in that field focuses on holonic/multi-agent control systems that couple predic-tive/proactive and reactive mechanisms into agents/holons. Meanwhile, not enough attention is paid to the optimization of this coupling. The aim of this paper is to depict the main research challenges that are to be addressed before expecting a large industrial dissemination. Relying on an extensive review of the state of the art, three main challenges are highlighted: the estimation of the future performances of the system in reactive mode, the design of efficient switching strategies between predictive and reactive modes and the design of efficient synchronization mechanisms to switch back to predictive mode.

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This special feature aims at shedding light on new emerging holonic and multi-agent systems operating in a service-and computing oriented manufacturing environment, using the latest ICT technologies such as service-orientation, mobile agents, Web-and Cloud services, virtualization, big data and analytics to name a few. Industrials are seeking for models and solutions that are not only able to provide efficient overall production performance, but also to face reactively a growing set of unpredicted events. The demand for large scale industrial systems running in complex and even chaotic environments requires the consideration of new paradigms and technologies that provide flexibility, robustness, agility and responsiveness. Holonic systems are, actually by definition, targeting challenges that include coping with the heterogeneous nature of manufacturing systems and their on-line interactive nature in combination with competitive pressures. Multi-agent systems is a suitable implementing approach to address these challenge by offering an alternative way to design control systems, based on the decentralization of control functions over distributed autonomous and cooperative entities. Moreover, virtualization of manufacturing execution system workloads offers a set of design and operational advantages to enterprises, the most visible being improved resource utilization and flexibility of the overall solution. At the manufacturing execution system level, cloud computing adoption refers mainly to virtualization of MES workloads. While MES implementations are different and usually depend directly on the actual physical shop floor layout, the general MES functions are aligned with the set of functions defined by ISA-95.03 specification. To achieve high levels of productivity growth and agility to market changes, manufacturers will need to leverage Big Data sets to drive efficiency across the networked enterprise. There is need for a framework allowing the development of manufacturing cyber physical systems that include capabilities for complex event processing and Big Data analytics, which are expected to move the manufacturing domain closer to digital transformation and cloud services within the contextual enterprise. On the other hand, service orientation is emerging at multiple organizational levels in enterprise business, and leverages technology in response to the growing need for greater business integration, flexibility and agility of manufacturing enterprises. Close related to IT infrastructures of Web Services, the Service Oriented Enterprise Architecture represents a technical architecture, a business modelling concept, an integration source and a new way of viewing units of control within the enterprise. Business and process information systems integration and interoperability are feasible by considering the customized product as "active controller" of the enterprise resources – thus providing consistency between material and informational flows. The areas of Service Oriented Computing and Multi-agent Systems are getting closer, both trying to deal with the same kind of environments formed by loose-coupled, flexible, persistent and distributed tasks. An example is the new approach of Service Oriented Multi-agent Systems (SoMAS).

Of interest are recent advances and on-going research in holonic and agent-based systems for manufacturing. Industrials are seeking for models and solutions that are not only able to provide efficient overall production performance, but also to face reactively a growing set of unpredicted events. One important research activity in the field focuses on holonic/multi-agent control systems that integrate predictive/proactive and reactive mechanisms into agents/holons. The demand for large scale systems running in complex and even chaotic environments requires the consideration of new paradigms and technologies that provide flexibility, robustness, agility and responsiveness. Holonic systems are, actually by definition, targeting challenges that include coping with the heterogeneous nature of manufacturing systems and their on-line interactive nature in combination with competitive pressures. Multi-agent systems is a suitable approach to address these challenge by offering an alternative way to design control systems, based on the decentralization of control functions over distributed autonomous and cooperative entities. Also, the concepts of Intelligent Product (or active product) and related techniques for product-driven automation are of interest.

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If the balancing problem during the design of assembly lines is widely studied in the literature under the name of ALBP (Assembly Line Balancing Problems), few works concern their rebalancing in a short term and on-line horizon. The work presented in this thesis focuses on the dynamic rebalancing of assembly lines in response to short-term events disrupting production. The objective is to change the allocation of tasks on the workstations in order to smooth the load induced by the disruption. The short delay without production stoppage being more important than the optimality of the solution, the fast resolution time of the approximate resolution methods interested us. Two approaches were studied for their simplicity and novelty in the ALBP domain: the Iterated Local Search (ILS) method and the reachability search on a network of communicating automata. This showed us that they can meet the need for reactivity imposed by our problem but that they are difficult to adapt when the action levers to rebalance the line are modified. Our proposal to meet this need for adaptability is a methodology for modeling and solving the problems of rebalancing assembly lines based on a network of communicating automata and a search for attainability on it. To ensure genericity, the methodology is decomposed into two levels of abstraction: the study of the class of the ALBP problem considered and the resolution of the specific problem. The work has been validated on industrial examples from the Trane company.

This CIFRE thesis is part of a collaboration between Acta-Mobilier, a manufacturer of high-end lacquered facades, and the Centre de Recherche en Automatique Nancy. The idea is to take advantage of the concept of Product Controlled System in an industrial environment disturbed by numerous production loops and by a non-negligible rate of rework (non-quality) generating losses of parts, non-respect of deadlines, unstable workloads, etc... the impossible link between the product and an infotronic identifier making traceability more difficult. Work on scheduling and its optimization is hampered by these disturbances in the production chain, which make schedules untenable. Priority treatment of defective parts ensures a service rate that remains remarkable in relation to the percentage of parts to be repaired. But this also leads to losses of parts that prevent the complete delivery of the order. The scientific problem is based on the management of flows in a context of production disrupted by rework and the control of quality by evaluating its impact on the bottleneck. The issue of quality control has been addressed using neural networks capable of predicting the appearance of the defect to which they are dedicated according to production and environmental parameters. This anticipation allows to propose an alternative program to use or to postpone the task planning. The adaptation of the prediction model to the drifts of the physical model to the behavior considered as nervous is carried out "on line" with the help of control charts that allow to detect the drift and its starting date. In spite of this simplification of the flows, the piloting remains complex because of the normal loops of production and the residual non qualities. There are different states of saturation of the system for which the most adapted control rule is not always the same. This analysis is presented in the form of a two-dimensional map, each axis of which presents a key indicator of the non-quality rate and/or flow disturbance. Even if, contrary to algorithms, the best adapted control rule will not always be highlighted, this cartography presents other advantages such as the simplification of the control, the possibility for all users to have the important information on the state of the workshop at a glance, or the need for homogenization on the whole production unit. In this context, the intelligent container offers interesting perspectives with the will to trace a group of products having the same manufacturing range rather than products one by one, to share information such as its delivery date, its degree of urgency, to know which paths they have to take in the workshop and which are the possible alternatives or to communicate with the machines and the other systems of which the one of forecast of the quality and to retain information in the course of the manufacture of the products. The proposed system is therefore interactive and the container is at the heart of the decision. It signals its presence to the scheduling system only if the quality conditions are met, thus simplifying its work and allowing a simple traditional linear programming algorithm to perform this task, which is particularly complicated at first glance. On the other hand, it is the scheduler's responsibility to ensure the steering rule to be used and to request the corresponding information from the available batches. The contribution of this thesis is therefore a methodology for simplifying complex problems by dividing the tasks between different actor subsystems applied to the case of a company manufacturing high-end lacquered kitchen fronts.

Nowadays, industrials are seeking for models and methods that are not only able to provide efficient overall production performance, but also for reactive systems facing a growing set of unpredicted events. One important research activity in that field focuses on holonic/multi-agent control systems that couple predictive/proactive and reactive mechanisms into agents/holons. Meanwhile, not enough attention is paid to the optimization of this coupling. The aim of this paper is to depict the main research challenges that are to be addressed before expecting a large industrial dissemination. Relying on an extensive review of the state of the art, three main challenges are highlighted: the estimation of the future performances of the system in reactive mode, the design of efficient switching strategies between predictive and reactive modes and the design of efficient synchronization mechanisms to switch back to predictive mode. indicator of the production system, discrete-event observer, flexible manufacturing system.

This paper introduces and opens the debate on the role of “product-driven control” and, on a broader level, Intelligent Manufacturing and Services Systems in sustainable development and circular economy. First, the concept of IMS and perspectives relating to future industrial and economic systems, as well as their expected advantages and the challenges to be addressed are introduced. Different interpretations of sustainability are then described. Third, our vision concerning the possible impacts of IMS on a sustainable world is presented. A set of challenging prospects and illustrative examples conclude this paper.

Nowadays, industrials are seeking for models and methods that are not only able to provide efficient overall production performance, but also reac-tive facing a growing set of unpredicted events. One important research activity in that field focuses on holonic/multi-agent control systems that couple predic-tive/proactive and reactive mechanisms into agents/holons. Meanwhile, not enough attention is paid to the optimization of this coupling. The aim of this paper is to depict the main research challenges that are to be addressed before expecting a large industrial dissemination. Relying on an extensive review of the state of the art, three main challenges are highlighted: the estimation of the future performances of the system in reactive mode, the design of efficient switching strategies between predictive and reactive modes and the design of efficient synchronization mechanisms to switch back to predictive mode.

The amount of data output in our environment is increasing each day, and the development of new technologies constantly redefines how we interact with information. In the context of PLM (Product Lifecycle Management), it is not uncommon to use intelligent products to ensure an information continuum all along the product life cycle (e.g. for traceability purposes). However, it is not that easy to identify what information should be stored on the product. To answer this question, this paper proposes a data dissemination process to select context- sensitive information from the database, that must be stored/replicated on the product (especially if the product is made of "communicating material"). Our approach uses the fuzzy AHP theory for aggregating points of view from different actors. The data dissemination process is then applied on a case study to embed context-sensitive information on a "communicating textile".

This paper proposes a method based on reachability search on a network of communicating automata. It is used to dynamically rebalance an assembly line when a disturbance occurs. The goal of the method is to dynamically reallocate the tasks on the workstations of this line. A network of automata is used to model the system and a solution is obtained by the trace provided by the model-checking software performing the reachability search. The method is illustrated on a case study.

This volume gathers the peer reviewed papers which were presented at the third edition of the International Workshop "Service Orientation in Holonic and Multi-agent Manufacturing and Robotics - SOHOMA'13" organized on June 20-22, 2013 by the Centre of Research in Computer Integrated Manufacturing and Robotics - CIMR Bucharest, and hosted by the University of Valenciennes, France. The book is structured in five parts, each one covering a specific research domain which represents a trend for modern manufacturing control: Distributed Intelligence for Sustainable Manufacturing, Holonic and Multi-Agent Technologies for Manufacturing Planning and Control. Service Orientation in Manufacturing Management and Control, Intelligent Products and Product-driven Automation and Robotics for Manufacturing and Services. These five evolution lines have in common concepts related to service orientation in a distributed planning and control agent-based industrial environment. today it is generally recognized that the Service Oriented Enterprise Architecture paradigm has been looked upon as a suitable and effective approach for industrial automation and management of manufacturing enterprises.

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This article proposes a method for dynamically rebalance an assem-bly line when disturbances occur, by reassigning the tasks to the line's work-stations. The method is based on reachability analysis of an automata network that represents the tasks and workstations to be performed. The execution trace leading to the desired state provides one feasible solution to rebalance the as-sembly line. The method is illustrated by an industrial case study.

Building Information Management systems have started to leverage new kinds of digital information infrastructures that integrate activities related to design, budgeting, scheduling, analysis, material management, and human resources. Companies implementing such systems have no other option today than exchanging information among themselves in a proper and efficient way. Industry foundation classes (IFCs) provide useful information structures for such a data sharing. However they do not specify how to capture, exchange and synchronize the information between distinct entities (i.e. information systems like sensors, servers, smart products…) throughout the building lifecycle. Accordingly, this paper investigates existing messaging protocols in order to identify which one is the most appropriate for supporting building lifecycle management. i.e a flexible protocol that provides sufficiently generic communication interfaces. A platform set up on a university campus based on the selected messaging protocol is then presented. Within this context, the research agenda that should be pursued to develop new techniques and algorithms for optimizing the building energy management is announced.

The amount of data output into our environment is increasing each day, and the development of new technologies constantly redefines how we interact with information. In the context of product life cycle management, it is not uncommon to use intelligent products to ensure an information continuum throughout the product life cycle (e.g., for traceability purposes). Integrating intelligence and information into products themselves is now possible through numerous technologies (RFID, communicating materials). However, these technologies currently have low memory capacities (several kilobytes or megabytes), whereas to product databases are becoming larger and larger (several gigabytes or terabytes). As a result, a data dissemination process is required to determine the relevant information that should be stored on the product. This paper proposes a multiple-criteria decision-making (MCDM) method based on a fuzzy Analytical Hierarchy Process (fuzzy AHP). This method is context-aware and supports the aggregation of opinions from a group of experts. An application is proposed to embed context-sensitive information in a "communicating textile".

This paper intends to provide an overview of the design approaches of simulation and modelling in Intelligent Manufacturing System (IMS) context. We focus on adaptive capability of the simulation models pushed by the introduction of new paradigms, i.e. intelligent product and Internet of Things. A Capability Maturity Model will be proposed for adaptive capability assessment and will be illustrated from our past researches. We will conclude discussing a set of challenging prospects.

The book covers four research domains representing a trend for modern manufacturing control: Holonic and Multi-agent technologies for industrial systems. Intelligent Product and Product-driven Automation. Service Orientation of Enterprise's strategic and technical processes. and Distributed Intelligent Automation Systems. These evolution lines have in common concepts related to service orientation derived from the Service Oriented Architecture (SOA) paradigm. The service-oriented multi-agent systems approach discussed in the book is characterized by the use of a set of distributed autonomous and cooperative agents, embedded in smart components that use the SOA principles, being oriented by offer and request of services, in order to fulfil production systems and value chain goals. A new integrated vision combining emergent technologies is offered, to create control structures with distributed intelligence supporting the vertical and horizontal enterprise integration and running in truly distributed and global working environments. The service value creation model at enterprise level consists into using Service Component Architectures for business process applications, based on entities which handle services. In this componentization view, a service is a piece of software encapsulating the business/control logic or resource functionality of an entity that exhibits an individual competence and responds to a specific request to fulfil a local (product) or global (batch) objective.

Intelligent products may be considered as information vectors, conveying their own information from a phase of its life cycle to another. Considering that such a product could be made with "communicating material", in previous work, a data dissemination process has been developed with the aim of selecting information from a database, that should be stored on the product according to the current stage of its life cycle. This selection is based on an indicator of relevance which depends on a multitude of criteria, whose weights are evaluated by a group of experts. The set of expert opinions must be formalized in accordance with a mathematical theory and then, synthesized by a suitable aggregation method. In this framework, three aggregation methods are introduced and compared. This comparison is carried out based on the scenario of data dissemination when using intelligent products. Results enable to assess the goodness of fit of the three aggregation methods.

In recent years, some scholars claimed the usage of intelligent products to make systems more efficient throughout the Product Life Cycle (PLC). Integrating intelligence and information into products themselves is possible with, among others, auto-ID technologies (barcode, RFID,.). In this paper, a new kind of intelligent product is introduced, referred to as "communicating material" paradigm. Through this paradigm, a product is i) capable of embedding information on all or parts of the material that it is made of, ii) capable of undergoing physical transformations without losing its communication ability and the data that is stored on it. This new material is used in our study to convey information between the different actors of the PLC, thus improving data interoperability, availability and sustainability. Although "communicating materials" provide new abilities compared to conventional products, they still have low memory capacities compared to product databases that become larger and larger. An information dissemination framework is developed in this paper to select the appropriate information to be stored on the product, at different stages of the PLC. This appropriateness is based on a degree of data relevance, which is computed by taking into account the context of use of the product (actor's expectations, environment,.). This framework also provides the tools to split information on all or parts of the material. A case study is presented, which aims at embedding context-sensitive information on "communicating textiles".

This chapter focuses on the concept of "product-driven control". First, this concept is introduced and the expected advantages and the problems to be solved are described. A brief but representative state of the art is presented. Several product-driven control applications in different domains are also used to illustrate the concept. This paper concludes with a set of challenging prospects.

New challenges and opportunities arise with the Internet of Things (IoT), making it possible to link any objects of the real world with the virtual one. In recent years, IoT has become increasingly popular in industrial applications (e.g. for the inclusion of data related to the product history). It might therefore be asked what is the impact on real-time applications when accessing data from the object instead of accessing it from the database. To assess that impact, this paper develops an approach that uses jointly two simulators: CPN Tools and OPNET Modeler. This approach is then applied on a benchmark scenario.

Keeping information in industries with divergent transformation processes has always posed important constraints, and the wood industry is no exception. The existing traceability solutions do not allow to keep this information throughout the life cycle of the wood product. The objective of this thesis is to show the feasibility of two concepts to improve information retention: the communicating material paradigm and the Virtual Manufacturing paradigm. With the first paradigm, it is possible to preserve the information related to the origin of the product thanks to a chemical marking introduced in the whole material that we identify by Nuclear Quadrupole Resonance. In the second paradigm, we anticipate the biometric characteristics of the final products by digitizing the material and virtualizing the transformation operations. Thanks to this, it is possible to determine, despite the imperfection of the data and decisions, the characteristics of the products.

This paper introduces and opens the debate on the place of "product-driven control" and, on a broader level, Intelligent Manufacturing and Services Systems in sustainable development and circular economy. First, IMS concept and perspectives on future industrial and economic systems, as well as their expected advantages and the challenges to be addressed are introduced. Different sustainability interpretations are then described. Third, our vision on possible impacts of IMS on a sustainable world is presented. This paper concludes with a set of challenging prospects.

Nowadays, intelligent products carrying information or having decision-making abilities are becoming widespread. The idea of using intelligent products to ensure an information continuum all along the product life cycle (PLC) is more and more shared today. However, it is not that easy to identify the information that must be linked to the product. As a result, this paper proposes an information dissemination process for selecting information sensitive to the context of use of the product. This information is then stored on the products themselves using a new type of augmented material, referred to as "communicating material".

New challenges and opportunities arise with the Internet of Things (IoT), making it possible to link any objects of the real world with the virtual one. In recent years, IoT has become increasingly popular in industrial applications (e.g. for the inclusion of data related to the product history). It might therefore be asked what is the impact on real-time applications when accessing data from the object instead of accessing it from the database. To assess that impact, this paper develops an approach that uses jointly two simulators: CPN Tools and OPNET Modeler. This approach is then applied on a benchmark scenario.

For many years, several communities such as IMS (Intelligent Manufacturing Systems), HMS (Holonic Manufacturing System) have suggested the use of intelligent products to make systems adaptable and adaptive and have shown the benefits that can be achieved, both at the economic level, in terms of product traceability, information sharing or optimization of manufacturing processes. However, a large number of questions remain open, such as the collection of product-related information, its storage throughout the supply chain, and the dissemination and management of this information throughout its life cycle. The contribution of this thesis consists in the definition of a framework for the dissemination of product information during the whole life cycle. This dissemination framework is associated with a new paradigm that radically changes the way of seeing the product and the material. This new concept consists in giving the product the ability to be intrinsically and integrally "communicating". The proposed information dissemination framework offers the possibility to the user to embed information sensitive to the context of use of the communicating product. In addition to the definition of the information dissemination process, this thesis offers an overview of the research fields, both scientific and technological, to be investigated in the future concerning the concept of "communicating matter".

The development of information and communication technologies in our century has greatly facilitated information exchange practices within supply chains. These practices have evolved into new forms of collaboration between companies, such as Information Sharing (IS) and Vendor Managed Inventory (VMI). VMI is a coordination mechanism in which the supplier is responsible for managing the inventory of its customer. This mechanism is based on several principles, among which is a highly developed sharing of information between the parties involved. IP and VMI are adopted by companies to increase profits and reduce costs. However, their results are mixed and require further understanding. The contribution of this thesis lies in the analysis of the impacts of these mechanisms on supply chains where all the links are production companies whose efficiencies may be different. To this end, several scenarios have been studied on logistics chains made up of three echelons, each echelon can belong to four efficiency classes. These chains can respond to two types of end-market demand: stable or variable demand. In addition, several coordination mechanisms are studied: standard management mechanisms, information sharing between two echelons, information sharing between three echelons, VMI between two echelons, and VMI extended to all three echelons. The tool used to conduct these experiments was the discrete event simulation software Arena. The interpretation of the results showed that the coordination mechanism with information sharing did not have a very significant improvement on the results. Indeed, since the companies have finite production capacities, the availability of information did not lead to different results. VMI, on the other hand, was able to achieve reductions in inventory and supply chain costs. These reductions were greater in supply chains with low efficiency links. In the latter case, both parties involved in the VMI (supplier and principal) benefited from the VMI. In the case of supply chains with high efficiency links, VMI has led to a smaller reduction in costs, as these supply chains are already high performance. In these cases, it is the customer who has benefited from VMI, while the VMI supplier has experienced an increase in costs due to the increased frequency of transport that this mechanism has involved.

This thesis recalls the fundamentals of logistics systems management and shows the interest of setting up a PCS (Product Controlled System). The integration of such systems must first take into account the coherence between the different elements that constitute it. Thus, centralized systems try to propose medium-long term plans aiming at an optimal cost, but also a certain stability and little nervousness in time. On the other hand, distributed systems have demonstrated their capacity to allow a rapid reaction to impromptu events occurring in the physical system. The hybridization of these two types of control is therefore a way to gain productivity for logistic and industrial systems. The first chapter of the thesis describes the evolution of production planning and control systems, with the objective of identifying the strengths and weaknesses of the different approaches proposed up to now and to define the general objective of the thesis. Chapter two analyzes the state of the art concerning the modeling tools for centralized/distributed production systems and also the concept of product control. This chapter serves as a basis for defining the specific objectives of the thesis. Chapter three presents the proposed modeling framework. This framework is based on a cybernetic approach, and more specifically on the viable system model (VSM). The chapter starts with a general presentation of the viable system model, then presents a generic model for modeling product-controlled systems. Finally, the chapter describes an application of this general framework to PCS-type production planning and control systems. Chapter four defines the different decision methods, both centralized and distributed, developed for the implementation of the generic model defined in chapter three. At the centralized and distributed levels these methods are based on mathematical programming models developed to consider the adaptability and flexibility of the system. Chapter five shows the main results in an application based on an industrial case that required the development of a simulation tool that considers short, medium and long term variables for the different optimization models. These results show the interest of this type of hybridization.

This work addresses the problem of endogenous control in Multi-Agent Systems (MAS) for solving complex problems, which we explore through the critical resource sharing problem. The so-called complex problems that we address are characterized by a combinatorial explosion of the number of solutions with the size of the problems, a strong dynamic of the problem data induced by an open environment in which many events can take place, a high systemic complexity resulting from the interdependencies between the numerous variables of the problem and finally a decentralization of the solving process imposed by a physical and functional distribution of the variables that is incompatible with a centralized vision of the problem. A complete survey of the search spaces associated with such problems is unrealistic in an acceptable time, it is then necessary to employ so-called incomplete resolution methods. Whatever the incomplete approach considered, the incomplete path of the search space requires control in order to maximize the probability of converging to a satisfactory solution. We identify three levels of control of the search space independently of the approach used: a static control (a priori definition of the system behavior), a dynamic control (evolving during the solution according to predefined mechanisms) and an adaptive control (evolving dynamically during the solution). We show that an endogenous control of the system's activity, i.e. an adaptive control stemming from the agents' own activity, is necessary to guide the path of the search space in the context of complex problem solving. These works have been realized in a context of industrial collaboration and are based on an approach developed in previous works: CESNA (Complex Exchanges between Stigmergic Negotiating Agents). CESNA is a self-organizing multi-agent approach exploiting agents located in an environment materializing the problem and exploited by a resolution process based on a stigmergic negotiation between the agents. The application case used by the CESNA approach to illustrate this work is the critical resource sharing problem, characterized by a limited set of resources exploited by a large number of consumers. Our contributions are of two types: first, we have proposed evolutions of the representation of the problem used by the initial approach (CESNA) in order to remove the limitations preventing a scaling up, and second, we have defined a new model (MANA: Multi-level bAlancing Negotiating Agents) using this new representation with a new resolution process based on endogenous mechanisms of control of the system activity. These mechanisms rely on the materialization of the microscopic effects of the macroscopic phenomenon to be guided (the path of the search space) in order to make it locally perceptible by the agents. Our measurements show that this new model allows the passage to scale (the resolution of large industrial problems) and a significant improvement of the resolution performances compared to the initial approach, thus showing the effectiveness of the guidance allowed by the mechanisms used.

The defended thesis is the result of a partnership between the Parisot group, and more particularly the Parisot Meuble company, and the TRACILOG technological research team of the Centre de Recherche en Automatique de Nancy. This work focused on a study of the opportunities brought by new information technologies on the processes of production management, as well as the proposal of a decision support system for the management of flows in the field. The proposed architecture is based on the infotronization of the flow of kanbans, which become "active kanbans" and ensure interoperability and synchronization between a centralized decision system and the various distributed decision entities, in order to coordinate all decisions. These proposals were validated using an emulation architecture, allowing the use of a control system in real conditions. Moreover, some of the proposed structures have been validated on the real production system. The contributions of this thesis work are based on : - The proposal of an architecture for the evaluation by emulation of production control systems, at an industrial scale, as well as the construction method. - The proposal of a production control support system to ensure the overall consistency of the decision system.

This thesis was realized in the framework of a partnership between CRAN and TRANE. It proposes a methodology for the integration and development of Product Controlled Systems (PCS). This methodology aims at implementing a control architecture by kanbans and/or "active" products, adaptable to the production systems of a company. The first chapter of the thesis describes the industrial context. At the end of this chapter, the flow synchronization problems of the company emerge. The second chapter presents a bibliographical study of the existing strategies of flow control and thus bringing elements of answer to these problems. After having shown the contribution of the product-controlled systems in the resolution of these problems, this chapter shows the need for engineering methods to design a PCS adapted "as closely as possible" to the industrial system studied. The third chapter is devoted to the definition of the scientific problem. In response to this, the proposal of a methodology for the design and integration of product-controlled systems is presented in the fourth chapter. This methodology is based on the "six-sigma" system engineering approach to drive the PCS design project by indicators coming from the users' needs. The use of event-driven simulation allows the design of the most relevant architecture with respect to the selected performance indicators and to validate a priori the integration of the SCP thus designed in its environment. The last chapter aims at illustrating the approach on real application cases.

The development of infotronic technologies, which allow data to be carried digitally by the product in order to give it an active role in the cybernetic loop, is leading to a questioning of the conventional organization of control systems, in order to move towards a product-based control. There is a large consensus on the interest of this approach in both centralized and distributed decision making. However, few works focus on the evaluation of the efficiency of product-based control in the interaction between centralized business-level information systems (ERP) and distributed process-level systems (MES). Our contribution focuses on a modeling and simulation tool for product-controlled control systems in order to evaluate different organizational topologies combining centralized and/or distributed decisions by comparing some productivity criteria. We first present the definition, the development and the validation of a component-oriented evaluation environment, based on an emulation tool and a multi-agent system, allowing to analyze the performances of a product-controlled system and to compare it with classical approaches. We then present the application of the product-based control from a series of experiments carried out with the developed environment. These experiments, carried out on an industrial case as well as on a laboratory experimentation platform, allow us to test and validate the feasibility of the concept of product-based control in terms of decisional impact and in terms of technical constraints.

Today, companies want to know how much to produce, when and in how much time? Moreover, they want to have a global vision of their production system and their logistics. Thus, the supply chain management is in charge of ensuring the reliability of the service level to the customers, while ensuring the best profitability for the company. We show in this thesis the interest of tactical planning and how to determine detailed plans, using a HPP structure. We propose a two-level disaggregation methodology that seeks to determine stable PDPs, taking into account robust and stable forecast plans. Optimization models are proposed as well as constraints that take into account decisions at each level, in order to ensure consistency between them. Finally, we apply a real demand processing model, using the AR process, to make the determined PDPs more stable.

The efficiency of companies depends on the degree of control of the production system. We have therefore sought to define a system that allows a better involvement of men in an integrated approach based on the knowledge of the production workshop experience. The positioning of this system encompasses improvement and efficiency actions. It contributes to helping managers in their search for the optimum benefit. It associates in the same approach the management of the material flows, the information flows, the production events of the daily realized with the remarks and/or ideas relative to these, expressed by the actors of a considered territory. By including in the regular production activities flexible methods of progress, the approach allows to induce new behaviors answering the expectations of the various actors of the company. The management strategy for the installation of the tool, posed as a hypothesis, has been validated in three application site companies, including a micro company, a SME, and a factory belonging to an international group. This strategy is based on a management matrix proposing a central axis of progress, a guideline for a three-phase implementation.