A method to envision highly constrained architectural zones in the design of multi-physics systems in severe conditions.

Summary 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. [.].