Using statistical-model-checking-based simulation for evaluating the robustness of a production schedule

Abstract : Industry 4.0 implies new scheduling problems linked to the optimal using of flexible resources and to mass customisation of products. In this context, first research results show that Discrete Event Systems models and tools are a relevant alternative to the classical approaches for modelling scheduling problems and for solving them. Moreover, the challenges of the industry 4.0 mean taking into account the uncertainties linked to the mass customisation (volume and mix of the demand) but also to the states of the resources (failures, operation durations,. . .). The goal of this paper is to show how it is possible to use the simulation based on statistical model checking for taking into account these uncertainties and for evaluating the robustness of a given schedule.
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Communication dans un congrès
7th Workshop on Service Orientation in Holonic and Multi-Agent Manufacturing, SOHOMA'17, Oct 2017, Nantes, France. 2017, 〈https://sohoma17.sciencesconf.org/〉
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Soumis le : mercredi 29 novembre 2017 - 23:33:38
Dernière modification le : jeudi 11 janvier 2018 - 06:24:15

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Sara Himmiche, Alexis Aubry, Pascale Marangé, Jean-François Pétin, Marie Duflot. Using statistical-model-checking-based simulation for evaluating the robustness of a production schedule. 7th Workshop on Service Orientation in Holonic and Multi-Agent Manufacturing, SOHOMA'17, Oct 2017, Nantes, France. 2017, 〈https://sohoma17.sciencesconf.org/〉. 〈hal-01652140〉

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