CE10 - Industrie et usine du futur : Homme, organisation, technologies

Design and control of reconfigurable and sustainable manufacturing systems – RECONFIDURABLE

Submission summary

Reconfigurable manufacturing systems (RMSs) are not only new manufacturing paradigm offering a customized flexibility. They are also a basis to develop a new generation of sustainable production systems. A promising way toward sustainable production passes through the design and intensive development of reconfigurable and sustainable manufacturing systems. The goal of this project is to develop an efficient methodology of decision-making support for the design and reconfiguration of such systems. The problem consists in an optimal selection of modules or pieces of equipment and an assignment of tasks to modules optimizing a given criterion while considering the required throughput and constraints as well as uncertainties. The project considers 3 main steps: design, reconfiguration and real-time control. For each of these 3 steps, we will develop and integrate sustainability criteria alongside conventional ones. In addition, two additional steps will be considered. The first represents a preliminary phase of identification and modeling of criteria to be evaluated and integrated. The second will be a test and validation step via industrial case studies. In this project, we will mainly focus on the environmental and economic dimensions of sustainability. So, our criteria will be technological (drift, quality, reliability), economical (cost, time, resources used), environmental (energy, emissions ...) and organizational (human factors, skills, safety and health ...). Our goal is not include all possible real life criteria but rather to propose an integrated approach of sustainability for design, planning and real-time reconfiguration of RMS while considering uncertainties. The techniques used will be based on multi-scale modeling, process modeling, combinatorial optimization and robust optimization as well as on stability analysis of the obtained solutions, discrete events simulation, and machine learning techniques.

Project coordination

Alexandre Dolgui (Laboratoire des Sciences du Numérique de Nantes)

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.

Partner

Kedge Business School / Operations Management and Information Systems Department
LS2N Laboratoire des Sciences du Numérique de Nantes
LIMOS Laboratoire d'Informatique, de Modélisation et d'Optimisation des Systèmes
LIS Laboratoire d'Informatique et Systèmes
ENSAM - LCFC Ecole Nationale Supérieure d'Arts et Mértiers - LABORATOIRE CONCEPTION FABRICATION COMMANDE
AI AUTOMATIQUE ET INDUSTRIE / Service R&D

Help of the ANR 580,208 euros
Beginning and duration of the scientific project: February 2022 - 48 Months

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