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  • 标题:Insurability of Cyber Physical Production Systems: How Does Digital Twin Improve Predictability of Failure Risk?
  • 本地全文:下载
  • 作者:Fazel Ansari ; Steffen Nixdorf ; Wilfried Sihn
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2020
  • 卷号:53
  • 期号:3
  • 页码:295-300
  • DOI:10.1016/j.ifacol.2020.11.063
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractOriginal equipment manufacturers (OEMs), machine operators and suppliers are three main stakeholders in today’s industrial asset management lifecycle. Considering high rate of investment and prices to purchase and operationalize secured IoT-based production systems, insurance companies explore contributing into industrial asset management lifecycle by providing new products to transparently monitor online condition and operation status of industrial machines, and accordingly adjust the insurance prices and offers. Hence, joint efforts and cross-disciplinary research is vital to introduce a new insurance product, i.e. failure-based insurance, gaining benefits from AI technologies and knowledge-based maintenance approaches. This paper provides insights into the aforementioned problem, and presents the work-in-progress research on failure-based insurance model aided by Digital Twin technology. Finally, the practical implications and future research directions are outlined.
  • 关键词:KeywordsCyber-Physical Production SystemsIndustry 4.0Intelligent maintenance systemsKnowledge discoveryAI for businesseconomyData driven decision making
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