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ASSISTANT: Learning and Robust Decision Support System for Agile Manufacturing Environments

Abstract : The European project ASSISTANT concept will provide a set of AI-based digital twins that helps process engineers and production planners to operate collaborative mixed-model assembly lines based on the data collected from IoT devices and external data sources. Such a tool will help planners to design the assembly line, plan the production, operate the line, and improve process tuning. In addition, the system monitors the line in real-time, ensures that all required resources are available, and allows fast re-planning when necessary. ASSISTANT aims to make cost-effective decisions while ensuring product quality, safety and wellbeing of the workers, and managing the various sources of uncertainties. The resulting digital twin systems will be data-driven, agile, autonomous, collaborative and explainable, safe but reactive.
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https://hal.archives-ouvertes.fr/hal-03486945
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Submitted on : Friday, December 17, 2021 - 2:56:15 PM
Last modification on : Friday, August 5, 2022 - 2:54:52 PM
Long-term archiving on: : Friday, March 18, 2022 - 7:18:48 PM

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Nicolas Beldiceanu, Alexandre Dolgui, Clemens Gonnermann, Gabriel Gonzalez-Castañé, Niki Kousi, et al.. ASSISTANT: Learning and Robust Decision Support System for Agile Manufacturing Environments. INCOM 2021: 17th IFAC Symposium on Information Control Problems in Manufacturing, Jun 2021, Budapest, Hungary. pp.641-646, ⟨10.1016/j.ifacol.2021.08.074⟩. ⟨hal-03486945v2⟩

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