The benefits of predictive maintenance in manufacturing excellence: a case study to establish reliable methods for predicting failures

被引:0
|
作者
Anwar Meddaoui
Mustapha Hain
Adil Hachmoud
机构
[1] Hassan II University,
[2] ENSAM,undefined
[3] Sidi Mohamed Ben Abdellah University,undefined
[4] EST,undefined
来源
The International Journal of Advanced Manufacturing Technology | 2023年 / 128卷
关键词
Predictive maintenance; Machine learning; Artificial Neural Network; Random Forest;
D O I
暂无
中图分类号
学科分类号
摘要
In the course of manufacturing excellence, decision makers are consistently confronted with the task of making choices that will enhance and meet industrial plant’s requirements. To this end, it is essential to maintain machines and equipment in a timely manner, which can prove to be one of the primary challenges. Predictive maintenance (PdM) strategy can enable real-time maintenance, providing numerous benefits such as reduced downtime, lower costs, and improved production quality. This article tries to demonstrate efficient physical parameters used in PdM field. The paper presents a case study operated in industrial production process to compare between the most used algorithm in predicting equipment failures. Future research can improve prediction accuracy with other artificial intelligence tools.
引用
收藏
页码:3685 / 3690
页数:5
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