文章基本信息

标题：Job Adjustment Strategy for Predictive Maintenance in Semi-Fully Flexible Systems Based on Machine Health Status
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作者：Thirupathi Samala ; Vijaya Kumar Manupati ; Bethalam Brahma Sai Nikhilesh 等
期刊名称：Sustainability
印刷版ISSN：2071-1050
出版年度：2021
卷号：13
期号：9
页码：5295
DOI：10.3390/su13095295
语种：English
出版社：MDPI, Open Access Journal
摘要：Complex systems consist of multiple machines that are designed with a certain extent of redundancy to control any unanticipated events. The productivity of complex systems is highly affected by unexpected simultaneous machine failures due to overrunning of machines, improper maintenance, and natural characteristics. We proposed realistic configurations with multiple machines having several flexibilities to handle the above issues. The objectives of the proposed model are to reduce simultaneous machine failures by slowing down the pace of degradation of machines, to improve the average occurrence of the first failure time of machines, and to decrease the loss of production. An approach has been developed using each machine’s degradation information to predict the machine’s residual life based on which the job adjustment strategy where machines with a lower health status will be given a high number of jobs to perform is proposed. This approach is validated by applying it in a fabric weaving industry as a real-world case study under different scenarios and the performance is compared with two other key benchmark strategies.