Using Genetic Algorithm to Robust Multi Objective Optimization of Maintenance Scheduling Considering Engineering Insurance

Efficient and on-time maintenance plays a crucial role in reducing cost and increasing the market share of an industrial unit. Preventive maintenance is a broad term that encompasses a set of activities aimed at improving the overall reliability and availability of a system before machinery breakdown. The previous studies have addressed the scheduling of preventive maintenance. These studies have computed the time and the type of preventive maintenance by modeling the total cost related to it. Todays the engineering insurance is an appropriate and durable protection for reducing the risks related to the industrial machinery. This kind of insurance covers a part of maintenance costs. Previous researches did not consider the effect of engineering insurance on maintenance scheduling while it affects the total cost function of maintenance scheduling seriously. Given the above-mentioned remarks, this paper introduces for the first time a new scheduling of preventive maintenance with considering total cost and total reliability of the system in which the effect of engineering insurance has been taken into account. Due to the uncertainty in the input parameters, which are very common in application, the paper proposed the application of robust design approaches. To solve this multi objective model, first it has been transformed into a single objective model by using global criterion and the resultant model is solved through genetic algorithm. The results show the magnitude effect of engineering insurance on maintenance scheduling. Therefore, neglecting the importance of engineering insurance leads to an inefficient scheduling maintenance.