Simple Time-to-Failure Estimation Techniques for Reliability and Maintenance of Equipment

被引:10
|
作者
Penrose, Howard W. [1 ,2 ,3 ]
机构
[1] Dreisilker Elect Motors Inc, Glen Ellyn, IL 60137 USA
[2] Univ Illinois, Chicago, IL USA
[3] UIC Energy Resources Ctr, Chicago, IL USA
关键词
Reliability and maintenance; time-to-failure estimation; reactive maintenance practices; predictive maintenance practices;
D O I
10.1109/MEI.2009.5191412
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
In 1979, MIT produced a report on maintenance with a focus on tribology. They estimated that $200 billion US dollars were spent on the direct costs associated with reliability and maintenance (R&M) [1]. At the time it was also estimated that over 14% of the 1979 gross domestic product (GDP) was lost opportunity due to improper R&M practices [2]. This level continued to increase as the industrial infrastructure aged, as well as other reliability-based reasons, to over 20% of the US GDP, or over $2.5 trillion in lost business opportunity [3]. This is greater than all but the top three economies in the world! At this time it is estimated that the R&M industry is approximately $1.2 trillion in size with up to $750 billion being the direct cost of breakdown maintenance (reactive) or generally poor, incorrect or excessive practices [4].The primary cause of the loss is that over 60% of maintenance programs are reactive, and the number is growing [2], which includes those programs which were initiated and later failed due to "maintenance entropy," or collapsing successful programs where the significant paybacks are no longer seen. At this time over 90% of maintenance initiatives fail, 57% of computerized maintenance management system (CMMS) applications fail, and over 93% of motor management programs fail [4]. The primary reason is that the present business mindset calls for immediate improvements, whereas it normally takes 12 to 24 months for a supported program to take hold and begin to show results - a rule of thumb that applies to all business practices. © 2009 IEEE.
引用
收藏
页码:14 / 18
页数:5
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