Warranty databases managed by most world-leading manufacturers are constantly expanding in the big data era. An important application of warranty databases is to detect unobservable reliability problems that emerge at design and/or manufacturing stages, through modeling and analysis of warranty claims data. Usually, serious reliability problems will result in certain abnormal patterns in warranty claims, which can be captured by appropriate statistical methods. In this article, a dynamic control charting scheme is developed for early detection of reliability problems by monitoring warranty claims one period after another, over the product life cycle. Instead of specifying a constant control limit, we determine the control limits progressively by considering stochastic product sales and non-homogeneous failure processes, simultaneously. The false alarm rate at each time period is controlled at a desired level, based on which abrupt changes in field reliability, if any, will be detected in a timely manner. Furthermore, a maximum-likelihood-based post-signal diagnosis scheme is presented to aid in identifying the most probable time of problem occurrence (i.e., change point). It is shown, through in-depth simulation studies and a real case study, that the proposed scheme is able to detect an underlying reliability problem promptly and meanwhile estimate the change point with an acceptable accuracy. Finally, a moving window approach concerning only recent production periods is introduced to extend the original model so as to mitigate the “inertia” problem.

In the business-to-consumer context, e.g., the automobile industry, preventive maintenance (PM) of warranted items usually relies upon customers to return their items to authorized maintenance centers according to prescribed schedules. However, item owners may be unpunctual, causing actual maintenance instants deviating from scheduled instants. This paper studies the impact of customer unpunctuality on the optimization of PM policy and the resultant warranty expenses. An unpunctual imperfect PM policy, which allows customers to advance or postpone scheduled PM activities in a tolerated range, is proposed for repairable items sold with a two-dimensional warranty. The expected total warranty costs of the unpunctual (and punctual) PM policies are derived under the assumption that customer unpunctuality is governed by a specific probability distribution. The optimization and comparison of the two policies are investigated in different scenarios regarding the product's failure rate function. The results for two possible unpunctuality distributions—uniform and triangular—are discussed and compared. Numerical studies show that the expected total warranty cost of the unpunctual policy could be either higher or lower than that of the punctual policy, depending on customer behaviors and the shape of failure rate function. Accordingly, manufacturers could induce customers to adjust their unpunctuality behaviors by modifying PM policies or introducing penalty/bonus mechanisms.

Nowadays, fierce competition and increasing customer requirements force manufacturers to continuously provide better after-sales services and supports. One such kind of after-sales services is product warranty which has been offered for almost all products in today's market. In this paper, we study a new warranty policy, called piece-wise renewing free replacement warranty. Under this policy, the whole warranty period is divided into two sub-periods and once an item fails in a specific sub-period, it will be replaced by a new identical one and the warranty period is fully or partially renewed. The expected warranty cost and warranty cycle of this policy are derived from the manufacturer's perspective. The proposed model is then modified by involving three sub-periods and a failure limit, respectively. In the latter scenario, when the number of item failures over a warranty cycle exceeds a pre-specified threshold, the manufacturer has to refund the item's purchase price, and consequently the warranty ceases. A real-world case study is presented using warranty data of a battery manufacturer. It is found that for a given warranty period, the piece-wise renewing free replacement policy has a better performance than traditional fully renewing policy, in terms of expected warranty cost, warranty cycle, and cost rate.

Reliability improvement strategies such as upgrade, reconditioning and remanufacturing have been extensively adopted by dealers of second-hand systems to improve the system reliability and reduce the warranty servicing cost. However, most existing studies on this topic do not consider the multi-component structures of complex second-hand systems, and either treat them as black-box systems by ignoring their internal structures or simply deal with individual components. In this paper, a new upgrade model is developed for complex second-hand systems sold with a non-renewing free repair/replacement warranty, by explicitly considering their multi-component configurations. Two types of components, i.e. repairable and non-repairable components, are taken into account. During the upgrade process, non-repairable components can be upgraded only by replacement (if necessary), while repairable ones may be imperfectly upgraded with various degrees. The main objective of the dealer is to determine which components to upgrade and the corresponding upgrade degrees, to minimise the total expected servicing cost. In view of the problem structure, a marginal analysis based algorithm is presented. It is shown that the proposed upgrade strategy contains the ‘no upgrade’ strategy and the ‘component-level perfect upgrade/replacement’ strategy as special cases, and outperforms them. Finally, several extensions of the proposed upgrade model are discussed.

In the context of equipment leasing, maintenance service is usually bundled with the leased equipment and offered by the lessor as an integrated package under a lease contract. The lessor is then responsible to prescribe an effective maintenance policy to keep the equipment operational in an economical way. This paper investigates upgrade and preventive maintenance (PM) strategies for industrial equipment during successive usage-based lease contracts with consideration of a warranty period, from the lessor's perspective. The accelerated failure time model and age reduction model are adopted to capture the effect of usage rate and imperfect PM/upgrade on the equipment reliability, respectively. More importantly, since equipment usage rates may vary across different lease contracts, this study develops an age correspondence framework to characterise usage rate shifts between successive lease periods. The optimal upgrade degree and the optimal number and level of PM actions are progressively updated for each upcoming lease period to minimise the total expected lease servicing cost, by considering the usage rate and maintenance implementation history. Numerical studies show that under given cost structures, periodical PM activities within each lease period tends to outperform the pre-leasing upgrade actions, though both of them can reduce the lease servicing cost.