文章基本信息

标题：Development of a flexible predictive maintenance system in the context of Industry 4.0
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作者：Vincent Ciancio ; Lazhar Homri ; Jean-Yves Dantan 等
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：1576-1581
DOI：10.1016/j.ifacol.2022.09.615
语种：English
出版社：Elsevier
摘要：Maintenance activities have changed over the recent years, through the digitalization of the field and the application of tools and concepts from Industry 4.0. By connecting and communicating with the production system, companies are now able to create knowledge about its current and future health state, allowing more and more efficient control over the equipment. This approach is called predictive maintenance, and its goal is to reduce unplanned downtimes and organize efficiently maintenance actions before failures and stoppages appear. However, to reach such performance, it is still quite challenging for the industrial actor to implement an Intelligent Maintenance System that will help with the data management. Therefore, this paper presents the approach that was used to develop and implement a predictive maintenance platform in the automotive industry context. This platform is built on open standards, and scalable regarding the different needs for data collect, storage, visualization, and analyses.
关键词：Condition Monitoring;Health monitoring;diagnosis;Industry 4.0;Intelligent maintenance systems;Internet of Things;Predictive maintenance