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  • 标题:Conceptual framework for smart maintenance based on distributed intelligence
  • 本地全文:下载
  • 作者:Terrin Pulikottil ; Luis A. Estrada-Jimenez ; Jose Barata
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2022
  • 卷号:55
  • 期号:19
  • 页码:121-126
  • DOI:10.1016/j.ifacol.2022.09.194
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractAn efficient maintenance strategy will provide more transparency and competitiveness for manufacturers in smart manufacturing era. Even though there have been several maintenance frameworks considering the emerging technologies, they still need to address challenges like big data storage, system resilience, multi-modality sensing, holistic approach, future-proof, generic framework and so on. To address these challenges, this paper presents a smart maintenance framework for shop-floor. First, a brief insight into key properties, performance indicators, levels and enablers of smart maintenance are described. The conceptual framework is based on distributed intelligence and has two major blocks - innate and adaptive intelligence. Tool wear monitoring is presented as a use case.
  • 关键词:KeywordsPredictive maintenancedistributed intelligencehuman immune systemsmart manufacturingtool wear monitoring
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