Non-periodic preventive maintenance policies for complex multi-component products sold with loss-based two-dimensional warranties

Abstract

Multi-component characteristics of complex industrial equipment, such as complex structures and stochastic dependencies, complicate analyzing the failure characteristics of such products and developing effective strategies to reduce warranty costs. In addition, a substantial customer loss or service interruption owing to the shutdown of these products forces manufacturers to formulate warranty contracts while considering customer loss. From the manufacturer’s perspective, with the aim of reducing the warranty costs while restraining the costs of customer loss, we propose the following two novel types of non-periodic imperfect preventive maintenance (PM) policies: unified and customized. The proposed PM policies simultaneously take into account the effects of customer usage rate heterogeneity and product deterioration on product failure. We characterize the failure relationship between the product and corresponding components based on the reliability block diagram and the Type I failure dependency model, and further construct the decision models for the proposed PM policies. The properties of the decision models are provided for certain special cases and are further used to design an algorithm for a general case. A comparison of the results of the numerical examples reveals the following: (1) Providing PM policies is beneficial for both the warranty providers and customers. The proposed PM policies are better than traditional periodic PM policies when shutdown loss costs are considered. (2) The stochastic dependencies will increase the costs of both the warranty and shutdown loss. It is necessary to take into account the stochastic dependencies of multi-component products when analyzing the warranty costs and formulating relevant decisions. (3) Beyond formulating effective PM policies, the manufacturer can mitigate the warranty cost pressure by adjusting the warranty coverage based on market information, or improving product reliability.