Customized Random Maintenance Policies After the Expiration of a Renewal Repair–Replacement Warranty with Random Charge

Driven by the trend of integrating monitored data into reliability management to explore innovative and practical approaches for managing reliability, researchers in the industry–university–research community have proposed random warranties. Existing random warranties use the limited mission cycle as a warranty-expiry limit instead of a measurement tool for controlling costs. This either shortens the warranty period for consumers or increases costs for manufacturers. To tackle these issues, this paper integrates mission cycles into the reliability management during the warranty stage and defines and models a renewal repair–replacement warranty with random charge (RRRW-RC) to manage the warranty-stage reliability of products. In the RRRW-RC, the limited mission cycles, acting as a usage limit, are used as a measurement tool to recover the fractional replacement cost within the warranty stage. This is designed to compensate manufacturers for replacement losses without shorting the warranty period, thus achieving the goal of reducing the warranty costs and not shortening the warranty period. The RRRW-RC can classify the usage habits of consumers into the heavy usage type and light usage type. Therefore, based on the usage classification results generated by the RRRW-RC, this paper also customizes two random maintenance policies to manage the post-warranty reliability of products. The first policy includes preventive/corrective replacement and “whichever occurs first,” and is thus referred to as customized bivariate random maintenance first (CBRMF). By revising “whichever occurs first” to “whichever occurs last,” the second policy is similarly represented and is called customized bivariate random maintenance last (CBRML). The policies defined above are modeled in terms of cost and time measures or cost rates, and their derivative policies are presented and modeled by setting parameter values. Numerical investigations are carried out to explore the management insights hidden in the proposed policies. Numerical investigations reveal that, by setting the failure number at an appropriate value, the warranty cost of the RRRW-RC can be minimized and its warranty period can be extended.