Optimum opportunistic maintenance schedule incorporating delay time theory with imperfect maintenance

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.