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  • 标题:XAI Sustainable Human in the Loop Maintenance
  • 本地全文:下载
  • 作者:Chris Turner ; Okechukwu Okorie ; John Oyekan
  • 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:67-72
  • DOI:10.1016/j.ifacol.2022.09.185
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThe field of Explainable Artificial Intelligence (XAI) is a relatively new approach to AI, with the aim to provide black box algorithms with human intelligible narrative functionality. It is most often in end-of-life considerations of the asset lifecycle that sustainability issues are encountered. Modern maintenance practice requires a holistic understanding of lifecycle and options for sustainable asset treatments. human in the loop solutions offer a way to leverage both machine and human skill sets to provide the next level of automaton solutions for industrial maintenance activities. This paper presents a framework for human in the loop Intelligent and Sustainable Maintenance. In bridging the gap between machines and humans XAI leverages the best of both worlds to provide a new level of agility to cyber assisted maintenance activities and full lifecycle consideration of assets; a notion that is necessary throughout the organization in the achievement of sustainability goals set by governments around the world in the achievement of a net zero carbon emission economy.
  • 关键词:KeywordsHuman in the loopIntelligent maintenance systemsIndustry 5.0Predictive maintenanceOperator 5.0
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