Preventive maintenance optimization for large-scale systems under life cycle cost

In view of the inadequacy of research on large-scale system maintenance strategies from the perspective of life cycle, this study proposes a new method for optimizing maintenance strategies in a large-scale system with homogeneous units that degrade over time. Specifically, assuming the unit failure obeys Weibull distribution, we consider the optimization model of imperfect grouping maintenance construct under the system reliability constraint. In the optimization model, the system life cycle cost is taken as the optimization target, and the preventive maintenance cycle and unit reliability are taken as the decision variables. Genetic algorithm was used to obtain the global optimal combination of decision variables at different maintenance improvement factor levels. The analysis results of typical examples show that the maintenance improvement factor is an important parameter that affects the life-cycle cost and reliability of the system. The results of this study can greatly simplify the decision-making process of engineers, and are more applicable to the formulation of maintenance strategies for large-scale systems requiring regular maintenance.