| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 10420007 | Reliability Engineering & System Safety | 2005 | 7 Pages |
Abstract
In real-world environments it is usually difficult to specify the quality of a preventive maintenance (PM) action precisely. This uncertainty makes it problematic to optimise maintenance policy. This problem is tackled in this paper by assuming that the quality of a PM action is a random variable following a probability distribution. Two frequently studied PM models, a failure rate PM model and an age reduction PM model, are investigated. The optimal PM policies are presented and optimised. Numerical examples are also given.
Related Topics
Physical Sciences and Engineering
Engineering
Mechanical Engineering
Authors
Shaomin Wu, Derek Clements-Croome,