Optimum opportunistic maintenance schedule incorporating delay time theory with imperfect maintenance

•Maintenance for multi-component system is scheduled due to inadequate failure data.•Deterioration process import delay time theory with inspection and failure data.•Multi-level maintenance activities are accommodated in executive schedule.•Opportunistic strategy is applied to grouping maintenance w...

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Vydáno v:Reliability engineering & system safety Ročník 213; s. 107668
Hlavní autoři: Liu, Gehui, Chen, Shaokuan, Jin, Hua, Liu, Shuang
Médium: Journal Article
Jazyk:angličtina
Vydáno: Barking Elsevier Ltd 01.09.2021
Elsevier BV
Témata:
Algorithms
Component reliability
Cost control
Delay time
Delay time theory
Downtime
Failure
Genetic algorithms
Imperfect maintenance
Inspection
Life cycles
Maintenance costs
Maintenance management
Multi-component systems
Opportunistic maintenance schedule
Optimization
Population genetics
Reliability analysis
Reliability aspects
Reliability engineering
Reliability threshold
Schedules
System effectiveness
Opportunistic maintenance schedule
Multi-component systems
Reliability threshold
Imperfect maintenance
Delay time theory
ISSN:0951-8320, 1879-0836
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Shrnutí:•Maintenance for multi-component system is scheduled due to inadequate failure data.•Deterioration process import delay time theory with inspection and failure data.•Multi-level maintenance activities are accommodated in executive schedule.•Opportunistic strategy is applied to grouping maintenance with reliability threshold.•A multi-population genetic algorithm is developed for a more efficient solution. A proper maintenance schedule is an effective solution to reduce failure and keep systems in good condition. Reliability evaluation and maintenance model are two key issues for schedule optimization. The delay time theory is applied to evaluate reliability for a system by using sufficient inspection data and insufficient failure data. An integrated maintenance optimization model is proposed to arrange multi-level maintenance actions for multi-component series systems. An optimization model for individual components is first developed to minimize the costs of maintenance, failure and downtime respectively over a life cycle of components. The opportunistic maintenance involving reliability thresholds is further imported to reduce the maintenance costs of whole system without any reduction of maintenance performance. An improved multi-population genetic algorithm is then employed to overcome the difficulty from the complexity of large-scale problems in practice. The applicability of model and efficiency of solution algorithm are finally testified through the case studies for a locomotive system where a time-based opportunistic maintenance schedule is carried out for comparisons. The proposed methodology is helpful for engineers and operators to achieve the performance improvement and cost savings of systems over maintenance durations.
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ISSN:0951-8320
1879-0836
DOI:10.1016/j.ress.2021.107668