Warranty Data Analysis: A Review

Warranty claims and supplementary data contain useful information about product quality and reliability. Analysing such data can therefore be of benefit to manufacturers in identifying early warnings of abnormalities in their products, providing useful information about failure modes to aid design modification, estimating product reliability for deciding on warranty policy and forecasting future warranty claims needed for preparing fiscal plans. In the last two decades, considerable research has been conducted in warranty data analysis (WDA) from several different perspectives. This article attempts to summarise and review the research and developments in WDA with emphasis on models, methods and applications. It concludes with a brief discussion on current practices and possible future trends in WDA

Two-Dimensional Product Differentiation Under Duopoly: An Application to Product and Service Reliability

Under oligopoly firms are often observed to specialise their production, with some firms producing highly reliable output and offering good warranty deals, while others produce less reliable output and offer less attractive warranties, but charge a lower price. This paper develops an approach to product/service reliability which provides an alternative to the conventional analysis based on the characteristics approach. The model of this paper defines reliability as the objective probability of product failure, not as a characteristic of individual goods. Reliability, thus defined, is treated as a choice variable of the firm, and consumers’ preferences are partially endogenised. This approach to reliability is incorporated into a duopoly model which explains the phenomenon of specialisation described above. The model is applicable to the markets for consumer durables, some intermediate goods and some services.Reliability, duopoly.

A system perspective on warranty problems within a supply chain

Thesis (S.M.)--Massachusetts Institute of Technology, System Design and Management Program, February 2005 [first author]; and, (S.M.)--Massachusetts Institute of Technology, System Design and Management Program, February 2006 [second author].Includes bibliographical references (p. 111-113).Warranty is important financially to American manufacturers, especially automotive companies. Carmakers and suppliers must work aggressively to improve their warranty management approach as warranty cost often equals or exceeds their investment in engineering. This thesis focuses on studying warranty management in a supply chain from a systems perspective. Warranty data in the automotive industry, focused upon a "Tier one" supplier, is analyzed to obtain general warranty trends and typical failure types. Following the data analysis and hypothesis formation, a sequential series of surveys and interviews within the supplier are conducted in attempt to determine the root causes of warranty failures. A major finding of the study is the lack of a cross-company and long-term approach for dealing with warranty. Other root causes (though not as deeply imbedded as that noted first) include the lack of design discipline, design knowledge, and resources in the product development process. In addition, unclear accountability, poor communication, and lack of a supplier management process delay the warranty resolution process. Furthermore, the culture and mindset in an organization is a critical element in effective warranty management. A reactive warranty firefighting mindset is inadequate to attack the significant warranty issues. Based upon solving the root causes found in the research, the thesis provides five specific recommendations. These recommendations appear likely to be useful to a wide variety of automotive companies as well as manufacturers in other industries.by Wei Shen and Wangquan (Winston) Cheng.S.M

Hazard rate models for early warranty issue detection using upstream supply chain information

This research presents a statistical methodology to construct an early automotive warranty issue detection model based on upstream supply chain information. This is contrary to extant methods that are mostly reactive and only rely on data available from the OEMs (original equipment manufacturers). For any upstream supply chain information with direct history from warranty claims, the research proposes hazard rate models to link upstream supply chain information as explanatory covariates for early detection of warranty issues. For any upstream supply chain information without direct warranty claims history, we introduce Bayesian hazard rate models to account for uncertainties of the explanatory covariates. In doing so, it improves both the accuracy of warranty issue detection as well as the lead time for detection. The proposed methodology is illustrated and validated using real-world data from a leading global Tier-one automotive supplier

Forecasting of Warranty Returns Based on the Reliability of Delivery Assessment

The paper presents a method to evaluate the reliability of deliveries with the application of Reliasoft Weibull++ software. The first stage in the proposed method was to collect data on outbound deliveries on a monthly basis and convert them into reliability data (life data). Next, by combining selected statistical tests and the maximum likelihood estimation method, the most accurate model of reliability of deliveries was obtained. Using the model which was generated, selected reliability indices were determined, such as: reliability of deliveries, unreliability of deliveries, failure rate of deliveries. Consequently, the number of future failed deliveries was forecast, taking into account the confidence bounds. The approach presented may be easily applied in companies in the logistics sector. The authors underlined that the reliability of deliveries is one of the key factors determining business competitiveness

Modeling the number of hidden events subject to observation delay

This paper considers the problem of predicting the number of events that have occurred in the past, but which are not yet observed due to a delay. Such delayed events are relevant in predicting the future cost of warranties, pricing maintenance contracts, determining the number of unreported claims in insurance and in modeling the outbreak of diseases. Disregarding these unobserved events results in a systematic underestimation of the event occurrence process. Our approach puts emphasis on modeling the time between the occurrence and observation of the event, the so-called observation delay. We propose a granular model for the heterogeneity in this observation delay based on the occurrence day of the event and on calendar day effects in the observation process, such as weekday and holiday effects. We illustrate this approach on a European general liability insurance data set where the occurrence of an accident is reported to the insurer with delay

Determining Optimal Reliability Targets Through Analysis of Product Validation Cost and Field Warranty Data

This work develops a new methodology to minimize the life cycle cost of a product using the decision variables controlled by a reliability/quality professional during a product development process. This methodology incorporates all product dependability-related activities into a comprehensive probabilistic cost model that enables minimization of the product's life cycle cost using the product dependability control variables. The primary model inputs include the cost of ownership of test equipment, forecasted cost of warranty returns, and environmental test parameters of a product validation program. Among these parameters, an emphasis is placed upon test duration and test sample size for durability related environmental tests. The warranty forecasting model is based on data mining of past warranty claims, parametric probabilistic analysis of the existing field data, and a piecewise application of several statistical distributions. The modeling process is complicated by insufficient knowledge about the relationship between product quality and product reliability. This can be attributed to the lack of studies establishing the effect of product validation activities on future field failures, overall lack of comprehensive field failure studies, and the market's dictation of warranty terms as opposed to warranties based on engineering rationale. As a result of these complicating factors an innovative approach to estimating the quality-reliability relationship using probabilistic methods and stochastic simulation has been developed. The overall cost model and its minimization are generated using a Monte Carlo method that accounts for the propagation of uncertainties from the model inputs and their parameters to the life cycle cost solution. This research provides reliability and quality professionals with a methodology to evaluate the efficiency of a product validation program from a life cycle cost point of view and identifies ways to improve the validation test flow by adjusting test durations, sample sizes, and equipment utilization. Solutions balance a rigorous theoretical treatment and practical applications and are specifically applied to the electronics industry

Determination of optimal pricing and warranty policies

An important problem facing manufacturers in today\u27s competitive market is the determination of the selling price of a product and its warranty period. A longer warranty may serve as a signal of product reliability; however, it may also lead to an increase in cost and hence reduce the profit if the product reliability is low. A burn-in test may be used to improve the reliability of products prior to their shipment.;This research presented integrated models for maximizing the expected profit for products that are subjected to a burn-in test and sold with warranty. The burn-in time, warranty period, and price were chosen as three decision variables in these models. The price and warranty period were treated as marketing variables and a simple multiplicative form was used to model their effect on sales. Solution procedures were developed for several warranty policies. These procedures are applicable for any failure time distribution. Three failure time distributions were further investigated and formulas for optimal solutions were derived. Finally, two sets of data were used to illustrate the application of the models. Two computer programs were developed to solve the models both parametrically and nonparametically

Some contributions to modeling usage sensitive warranty servicing strategies and their analyses

Providing a warranty as a part of a product\u27s sale is a common practice in industry. Parameters of such warranties (e.g., its duration limits, intensity of use) must be carefully specified to ensure their financial viability. A great deal of effort has been accordingly devoted in attempts to reduce the costs of warranties via appropriately designed strategies to service them. many such strategies, that aim to reduce the total expected costs of the warrantor or / and are appealing in other ways such as being more pragmatic to implement - have been suggested in the literature. Design, analysis and optimization of such servicing strategies is thus a topic of great research interest in many fields. In this dissertation, several warranty servicing strategies in two-dimensional warranty regimes, typically defined by a rectangle in the age-usage plane, have been proposed, analyzed and numerically illustrated. Two different approaches of modeling such usage sensitive warranty strategies are considered in the spirit of Jack, Iskandar and Murthy (2009) and Iskandar (2005). An `Accelerated Failure Time\u27 (AFT) formulation is employed to model product degradation resulting due to excessive usage rate of consumers. The focus of this research is on the analysis of warranty costs borne by the manufacturer (or seller or third party warranty providers) subject to various factors such as product\u27s sale price, consumer\u27s usage rate, types and costs of repair actions. By taking into account the impact of the rate of use of an item on its lifetime, a central focus of our research is on warranty cost models that are sensitive to the usage rate. Specifically, except the model in Chapter 4 where the rate at which an item is used is considered to be a random variable; all other warranty servicing policies that we consider, have usage rate as a fixed parameter, and hence are policies conditional on the rate of use. Such an approach allows us to examine the impact of a consumer\u27s usage rate on the expected warranty costs. For the purpose of designing warranties, exploring such sensitivity analysis may in fact suggest putting an upper limit on the rate of use within the warranty contract, as for example in case of new or leased vehicle warranties. A Bayesian approach of modeling 2-D Pro-rated warranty (PRW) with preventive maintenance is considered and explored in the spirit of Huang and Fang (2008). A decision regarding the optimal PRW proportion (paid by the manufacturer to repair failed item) and optimal warranty period that maximizes the expected profit of the rm under different usage rates of the consumers is explored in this research. A Bayesian updating process used in this context combines expert opinions with market data to improve the accuracy of the parameter estimates. The expected profit model investigated here captures the impact of juggling decision variables of 2-D pro-rated warranty and investigates the sensitivity of the total expected profit to the extent of mis-specification in prior information