Abstract
This study designs extended warranty strategy for engineering equipment by considering the warranty cost and availability requirement. Aiming to minimize the cost rate and maximize the availability simultaneously, a multi-objective maintenance optimization model is established. Various maintenance modes are adopted, including minimal maintenance, replacement and imperfect maintenance based on dynamic improvement factors. The failure rate threshold and replacement cycle are taken as the decision variables. By using the fast elite non-dominated sorting genetic algorithm (NSGA-II), the Pareto optimal solutions of extended warranty policies are obtained. Case study is implemented to illustrate the validity of the optimization model. It shows that compared with single-objective optimization, multi-objective optimization can achieve a lower cost rate and higher availability. Meanwhile, it can obtain better and more optimization results to promote the flexibility of the warranty policies.
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