4.7 Article

A new preventive maintenance strategy optimization model considering lifecycle safety

Journal

RELIABILITY ENGINEERING & SYSTEM SAFETY
Volume 221, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.ress.2022.108325

Keywords

Preventive maintenance; Maintenance strategy; Lifecycle failure probability; Expected cost of failure; Surrogate model

Funding

  1. National Natural Science Foundation of China [51475370, 51775090]
  2. National Major Science and Technology Projects of China [2017-IV-0009-0046]

Ask authors/readers for more resources

This study establishes a general preventive maintenance strategy optimization (PMSO) model for structures by estimating reliability and considering the lifecycle safety under maintenance, providing a comprehensive approach to maintenance strategy.
Preventive maintenance can improve the structure reliability at the same time balance the cost, thus it has gained widespread concern during the past decades. This work focuses on establishing a general preventive maintenance strategy optimization (PMSO) model for structure by deeply exploring the effect of maintenance on structure performance function, with which the reliability is estimated instead of directly assuming a reliability function for structure. At the same time, the lifecycle safety of structure under maintenance is employed to identify the maintenance strategy since it can provide the solution by considering the different operation time intervals as a whole so that people can fully grasp the maintenance effect. This model is established by decomposing the lifecycle failure state as different failure states or conditional failure states during different operation time intervals, and lifecycle failure probability is finally described by the joint time-dependent failure probability of different operation time intervals after further derivation. Furthermore, an advanced estimation strategy is proposed, in which only one surrogate model is construct and it can accurately estimate the failure probabilities of different performance functions. Then, a two-level surrogate model is further constructed to deal with the difficulties of optimization and stochastic simulation variability in identifying the optimal maintenance time. Several engineering applications are employed to show the effectiveness of the established PMSO model and strategy.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available