Abstract
This chapter presents a generic methodology when considering robustness in production systems of Industry 4.0. It is the first milestone for coupling Operations Research models for robust optimization and Discrete Event Systems models and tools for property checking. The idea is to iteratively call Operations Research and Discrete Event Systems Models for converging towards a solution with the required robustness level defined by the decision-maker.
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Acknowledgements
This chapter is the result of a collaboration between the two working groups BermudesFootnote 1 and SEDFootnote 2 from the French National Centre for Scientific Research (CNRS).
The Bermudes group has been created in 1996. It is labeled by the GDR ROFootnote 3 and the GDR MACS Footnote 4, which are two research groups depending on the French CNRS. Focused at the beginning on classical scheduling issues such as classical scheduling workshop problems (Job Shop, Flow Shop, Generalized Job Shop, Hybrid Flow Shop, etc.), scheduling problems in manufacturing systems (Flexible Manufacturing Systems, Hoist Scheduling Problems), and Resource Constrained Project Scheduling Problems, its research topics have evolved following Industry 4.0 context and include now integrated scheduling problems taking into account both several related activities (maintenance, transport, etc.) and different constraints (environmental, human, energetic, etc.). Determination of robust or reactive scheduling has become an important issue.
The Discrete Event Systems Working Group (DES) has been created in 2014. It is a French working group from the GDR MACS. Its objectives are to promote exchanges between the various specialists, whether they come from the world of automation, computer science, or mathematics, and thus to provide a better knowledge of the problems related to DES and the solutions that can be provided. The topics covered include (1) the study of the syntax and semantics of DES formalisms; (2) the application of these formalisms for modeling based on specifications, system performance analysis, simulation, property verification, system control, supervision, observation, detection, diagnosis, decision support, architecture selection, reconfiguration, etc.
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Marangé, P. et al. (2020). Coupling Robust Optimization and Model-Checking Techniques for Robust Scheduling in the Context of Industry 4.0 . In: Sokolov, B., Ivanov, D., Dolgui, A. (eds) Scheduling in Industry 4.0 and Cloud Manufacturing. International Series in Operations Research & Management Science, vol 289. Springer, Cham. https://doi.org/10.1007/978-3-030-43177-8_6
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