Properties of Lifetime Estimators Based on Warranty Data Consisting only of Failures

Nowadays, many consumer durable goods, such as, automobiles, appliances, and photocopiers etc., are sold with manufacturer’s warranty to insure product quality and reliability. Warranty claims contain a large amount of useful information about reliability of the products, such as, failure times, usage, and failure modes etc. For engineering purposes, usage is more relevant, and hence, modeling usage accumulation is of great interest in reliability analysis using warranty data. Such models are needed to manufacturers to evaluate reliability, predict warranty costs, and to assess design modification and customer satisfaction. Usually, warranty data consists of only failure information, and non-failure information is not obtainable which makes the reliability analysis difficult. The sales data is also important for reliability analysis as it contains time-in-service in calendar timescale for each non-failed product during the warranty plan. This chapter discusses maximum likelihood estimation of lifetime parameters using warranty data along with sales data and examines the precision of the estimators by the asymptotic variances obtained from Fisher Information Matrix. The practical consequence of this finding is that the proposed method produces estimators of the lifetime parameters with good precision for large sales amount.