Customer-Rush Near Warranty Expiration Limit, and Nonparametric Hazard Rate Estimation From Known Mileage Accumulation Rates

Abstract

Time or mileage data obtained from warranty claims are generally more accurate for hard failures than for soft failures. For soft failures, automobile users sometimes delay reporting the warranty claim until the warranty coverage is about to expire. This results in an unusually high number of warranty claims near the end of warranty coverage. Because such a phenomenon of customer-rush near the warranty expiration limit occurs due to user behavior rather than due to the vehicle design, it creates a bias in the warranty dataset. Design improvement activities that use field reliability studies based on such data can potentially obtain a distorted picture of the reality, and lead to unwarranted, costly design changes. Research in the area of field reliability studies using warranty data provides several methods for warranty claims resulting from hard failures, and assumes reported time or mileage as actual time or mileage at failure. In this article, the phenomenon of customer-rush near the warranty expiration limit is addressed for arriving at nonparametric hazard rate estimates. The proposed methodology involves situations where estimates of mileage accumulation rates in the vehicle population are available. The claims influenced by soft failures are treated as left-censored, and are identified using information in technician comments about the repair carried out plus, if required, a more involved engineering analysis of field returned parts. Maximum likelihood estimates for the hazard function and their confidence limits are then obtained using Turnbull's iterative procedure. An application example illustrates use of the proposed methodology