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

Abstract

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