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A high‐performance maintenance strategy for stochastic selective maintenance
Author(s) -
Zhao Jing,
Liu Jianqi,
Zhao Zhenting,
Xin Miao,
Chen Yu
Publication year - 2018
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.4840
Subject(s) - reliability (semiconductor) , reliability engineering , computer science , constraint (computer aided design) , optimal maintenance , limit (mathematics) , preventive maintenance , time constraint , predictive maintenance , work (physics) , operations research , mathematical optimization , engineering , mathematics , mechanical engineering , mathematical analysis , power (physics) , physics , quantum mechanics , political science , law
Summary Selective maintenance is often applied in many industrial environments where maintenance is performed between sequence missions. When the mission time is stochastic and there are multiple maintenance workers with different capacities, the system reliability of the next work mission can be maximized by using a stochastic model under the constraint of the limit maintenance time. The optimal maintenance strategy is obtained with an optimization algorithm. A simulation was performed to verify the validity and feasibility of the proposed model.