Predictive Maintenance of Server using Machine Learning and Deep Learning

被引:0
作者
Yeole, Anjali
Mane, Dashrath
Gawali, Mahindra
Lalwani, Manas
Chetwani, Mahindra
Suryavanshi, Parth
Anala, Harshita
机构
关键词
Sever; Failure; Predictive Maintenance; Machine Learning;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
- Traditional IT maintenance often leads to wasted resources and downtime. This paper explores how predictive maintenance (PdM) with machine learning can revolutionize server management in Industry 4.0. By comparing various machine learning models for PdM, we analyze their effectiveness in predicting server failures. The paper emphasizes the critical role PdM plays in boosting server reliability and driving industry transformation, supported by statistics highlighting its growing importance. Furthermore, we bridge the theory-practice gap by proposing a web application specifically designed for server PdM, allowing for proactive maintenance and reduced downtime. Finally, we explore future research directions and emerging trends in server PdM, providing valuable insights for organizations seeking to optimize maintenance practices and achieve operational excellence in the digital age.
引用
收藏
页码:2828 / 2833
页数:6
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