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  • 标题:ASSISTANT: Learning and Robust Decision Support System for Agile Manufacturing Environments
  • 本地全文:下载
  • 作者:Nicolas Beldiceanu ; Alexandre Dolgui ; Clemens Gonnermann
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2021
  • 卷号:54
  • 期号:1
  • 页码:641-646
  • DOI:10.1016/j.ifacol.2021.08.074
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThe European project ASSISTANT 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.
  • 关键词:KeywordsArtificial intelligenceData analyticsDigital twinsDecision aidReconfigurable manufacturing systemsProcessproduction planningSchedulingreal-time control
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