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  • 标题:Data-driven decision process for robust scheduling of remanufacturing systems
  • 本地全文:下载
  • 作者:Michael Schlecht ; Sara Himmiche ; Virginie Goepp
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2022
  • 卷号:55
  • 期号:10
  • 页码:755-760
  • DOI:10.1016/j.ifacol.2022.09.500
  • 语种:English
  • 出版社:Elsevier
  • 摘要:Robust scheduling problem is a major decision problem that is addressed in the literature, especially for remanufacturing systems; this problem is complex because of the high uncertainty and complex constraints involved. Generally, the existing approaches are dedicated to specific processes and do not enable the quick and efficient generation and evaluation of schedules. With the emergence of the Industry 4.0 paradigm, data availability is now considered an opportunity to facilitate the decision-making process. In this study, a data-driven decisionmaking process is proposed to treat the robust scheduling problem of remanufacturing systems in uncertain environments. In particular, this process generates simulation models based on a data-driven modeling approach. A robustness evaluation approach is proposed to answer several decision questions. An application of the decision process in an industrial case of a remanufacturing system is presented herein, illustrating the impact of robustness evaluation results on real-life decisions.
  • 关键词:data-driven modeling;simulation;decision making;remanufacturing;scheduling;robustness evaluation
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