文章基本信息

标题：XAI Sustainable Human in the Loop Maintenance
本地全文：下载
作者：Chris Turner ; Okechukwu Okorie ; John Oyekan 等
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