Abstract
The warranty datasets available for various car models are characterized by extremely imbalanced classes, where a very low amount of under-warranty vehicles have at least one matching claim (“failure”) of a given type. The failure probability estimation becomes even more complex in the presence of censored warranty data, where some of the vehicles have not reached yet the upper limit of the predicted interval. The actual mileage rate of under-warranty vehicles is another source of uncertainty in warranty datasets. In this paper, we present a new, continuous-time methodology for failure probability estimation from multi-dimensional censored datasets in automotive industry.
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References
Chukova, S., Robinson, J.: Estimating mean cumulative functions from truncated automotive warranty data. In: Wilson, A., Limnios, N., Keller-McNulty, S., Armijo, Y. (eds.) Mathematical and Statistical Methods in Reliability. Series on Quality, Reliability and Engineering Statistics, pp. 121–136. World Scientific, Singapore (2005)
Hu, X.J., Lawless, J.F., Suzuki, K.: Nonparametric estimation of a lifetime distribution when censoring times are missing. Technometrics 40, 3–13 (1998)
Majeske, K.D.: A non-homogeneous Poisson process predictive model for automobile warranty claims. Reliab. Eng. Syst. Safe 92, 243–251 (2007)
Wu, S.: Warranty Data Analysis: A Review. Qual. Reliab. Eng. Int. (published online first, 2012)
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© 2013 Springer-Verlag Berlin Heidelberg
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Last, M., Zhmudyak, A., Halpert, H., Chakrabarty, S. (2013). Multi-dimensional Failure Probability Estimation in Automotive Industry Based on Censored Warranty Data. In: Kruse, R., Berthold, M., Moewes, C., Gil, M., Grzegorzewski, P., Hryniewicz, O. (eds) Synergies of Soft Computing and Statistics for Intelligent Data Analysis. Advances in Intelligent Systems and Computing, vol 190. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33042-1_54
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DOI: https://doi.org/10.1007/978-3-642-33042-1_54
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33041-4
Online ISBN: 978-3-642-33042-1
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