Optimal warranty design and post-warranty maintenance for products subject to stochastic degradation

Warranty policy, as a marketing strategy, has been widely studied for several decades, but warranty models incorporating condition-based maintenance are still rare. In condition monitoring, product reliability in the warranty period can be tracked and predicted based on its degradation path. In this article, we first propose a condition-based renewable replacement warranty policy through the integration of Inverse Gaussian degradation model. The goal is to maximize the manufacturer's profit by optimizing the warranty period, sale price, and replacement threshold. In a monopoly market, we show that it is more profitable to let the replacement threshold equal the failure threshold. However, in the competitive market the optimal replacement threshold should be below and no more than the failure threshold. Second, depending on whether the historical degradation level is observable or not to the customer, optimal post-warranty maintenance policy considering hybrid preventative maintenance effect (i.e., both age and degradation level reduction) is derived. Numerical experiments show that a larger replacement threshold can increase the manufacturer's profit, reduce sale price and prolong warranty period, but it has less effect on saving the consumer's cost or extending the replacement age.