TY - JOUR
T1 - A new preventive maintenance strategy optimization model considering lifecycle safety
AU - Shi, Yan
AU - Lu, Zhenzhou
AU - Huang, Hongzhong
AU - Liu, Yu
AU - Li, Yanfeng
AU - Zio, Enrico
AU - Zhou, Yicheng
N1 - Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/5
Y1 - 2022/5
N2 - 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.
AB - 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.
KW - Expected cost of failure
KW - Lifecycle failure probability
KW - Maintenance strategy
KW - Preventive maintenance
KW - Surrogate model
UR - http://www.scopus.com/inward/record.url?scp=85123776014&partnerID=8YFLogxK
U2 - 10.1016/j.ress.2022.108325
DO - 10.1016/j.ress.2022.108325
M3 - 文章
AN - SCOPUS:85123776014
SN - 0951-8320
VL - 221
JO - Reliability Engineering and System Safety
JF - Reliability Engineering and System Safety
M1 - 108325
ER -