Accelerated testing is often used to gauge the reliability of a product before it is released to the market. Warranty data provide valuable additional information about the reliability of a product and its constituent components via field data. In this study, warranty data provided by an Australian automobile manufacturer is used. This article considers the need to clean the data before commencing any analysis. It discusses the distribution of warranty claims and the use of warranty data to model the reliability of elemental components of an automobile. Various model options are considered before suitable modelling is adopted. The reality of modelling the reliability of a vehicle containing a large number of components is considered and a suitable method is adopted. Verification of the reliability modelling is made by comparing an estimated warranty cost with the actual cost. References Blischke, W. R., Karim, M. R. and Murthy, D. N. P. Warranty Data Collection and Analysis. Springer, London, 2011. Blischke, W. R. and Murthy, D. N. P. Warranty Cost Analysis. Marcel Dekker, Inc, New York, 1994. Blischke, W. R. and Murthy, D. N. P. Reliability: Modelling, Prediction, and Optimisation. John Wiley and Sons, New York, 2000. Campean, I. F. and Brunson, D. Reliability modelling using warranty data. International Conference on Statistics and Analytical Methods in Automotive Engineering. IMechE Conference Transactions 2002, 225--236. Cox, D. R. Renewal Theory. Chapman and Hall, New York, 1982. Cox, D. R. and Oakes, D. Analysis of Survival Data. Chapman and Hall, London, 1984. Hill, V. L. and Blischke, W. R. An assessment of alternative models in warranty analysis. Journal of Information and Optimization Sciences, 8, 1987, 33--55. Iskandar, B. P. and Blischke, W. R. Reliability and Warranty Analysis of a Motorcycle Based on Claims Data. In Case Studies in Reliability and Maintenance (eds W. R. Blischke and D. N. P. Murthy.) John Wiley and Sons, Hoboken, NJ, USA, 2003, 623--656. doi:10.1002/0471393002.ch27 Lawless, J. F. Statistical Models and Methods for Lifetime Data. John Wiley and Sons, New York, 1982. Lawless, J. F., Hu, J. and Cao, J. Methods for the estimation of failure distributions and rates from automobile warranty data. Lifetime Data Analysis, 1, 1995, 227--240. Lu, M. Automotive reliability prediction based on early field failure warranty data. Quality And Reliability Engineering International, 14, 1998, 103--108. doi:10.1002/(SICI)1099-1638(199803/04)14:2<103::AID-QRE147>3.0.CO;2-5 Majeske, K. D. Evaluating product and process design changes with warranty data. International Journal of Production Economics, 50, 1997, 79--89. doi:10.1016/S0925-5273(97)00034-0 Majeske, K. D. and Herrin, G. D. Determining the warranty benefits for automobile design changes. Proceedings Annual Reliability and Maintainability Symposium, 1998, 94--99. http://ieeexplore.ieee.org/xpls/abs\protect \global \let \OT1\textunderscore \unhbox \voidb@x \kern .06em\vbox {\hrule width.3em}\OT1\textunderscore all.jsp?arnumber=653636andtag=1 Nelson, W. Applied Life Data Analysis. John Wiley and Sons, New York, 1982. Rai, B. and Singh, N. Hazard rate estimation from incomplete and unclean warranty data. Reliability Engineering and System Safety, 81, 2003, 79--92. doi:10.1016/S0951-8320(03)00083-8 Singh, N. and Rai, B. K. Reliability Analysis and Prediction with Warranty Data: Issues, Strategies, and Methods. CRC Press, 2009. doi:10.1201/9781439803264 Summit, R. Estimating the reliability model parameters through a simulation of warranty claims: How much data is needed? ANZIAM Journal, 53, 2011. http://journal.austms.org.au/ojs/index.php/ANZIAMJ/article/view/5114 Tijms, H. C. Stochastic Models: An Algorithmic Approach. John Wiley and Sons, New York, 1994. Xie, M. On the Solution of Renewal-Type Integral Equations. Communications in Statistics, 18, 1989, 281--293. doi:10.1080/03610918908812760