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Warranty Cost Estimation using K-Means Cluster Analysis for Automobile Industry:Technical Note
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When a vehicle under warranty comes for service, the technician identifies the potential fault and the corresponding service is done. From the raw information of customer complaint, the complaint codes are identified and allocation of qualified technician involves considerable man hours and cost per hour for the technician to do the service. Around 1059 vehicles under warranty were studied starting from customer complaint to the study of warranty cost to the manufacturer. In this paper, initially, we present the results of classifying the complaint code master into several classes using K-means cluster analysis and subsequently cluster analysis for a specific component say, water pump assembly was carried out. Then, analysis of cost to the automobile manufacturer on warranty claims are also presented here.
Keywords
Automobile, Cluster, Warranty, Estimation, Cost Analysis.
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- J.A. Mueller and F. Lemke. 2009. Self-organising data mining: An intelligent approach to extract knowledge from data, Script Software Int., Berlin, 62-71.
- S.P. Singh, S.S.P. Shukla, N. Rakesh and V. Tyagi. 2011. Problem reduction in online payment system using hybrid model, Int. J. Managing Information Tech., 3(3), 62-70.
- R. Patidar and L. Sharma. 2011. Credit card fraud detection using neural network, Int. J. Soft Computing and Engg., 1, 32-38.
- M.R. Karim and K. Suzuki. 2005. Analysis of warranty claim data: A literature review, Int. J. Quality and Reliability Management, 22(7), 667-686. https://doi.org/10.1108/02656710510610820
- S. Wu. 2012. Warranty data analysis: A review, Quality and Reliability Engg., 28(8), 795-805. https://doi.org/10.1002/qre.1282
- J.D. Kalbfleisch and J.F. Lawless. 1996. Statistical Analysis of Warranty Claims Data, Product Warranty Handbook, New York, 231-259.
- Warranty Cost Analysis. 2006. Warranty management and product manufacture, Springer Series in Reliability Engg., Springer, London, 2006.
- R. Srinivasan, S. Manivannan and S.P. Devi. 2015. A critical review paper on warranty analysis for fleet industry using data mining techniques, Int. J. Applied Engg. Research, 10(55), 1132-1134.
- R. Srinivasan, S. Manivannan, N. Ethiraj, S.P. Devi and S.V. Kiran. 2016. Modelling an optimized warranty analysis methodology for fleet industry using data mining clustering methodologies with fraud detection mechanism using pattern recognition on hybrid analytic approach, Proc. Computer Science, 87, 322-327. https://doi.org/10.1016/j.procs.2016.06.001.
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