Open Access Open Access  Restricted Access Subscription Access

Warranty Cost Estimation using K-Means Cluster Analysis for Automobile Industry:Technical Note


Affiliations
1 Mech. Engg. Dept., Dr. M.G.R Educational and Research Institute, Tamil Nadu, India
2 Dept. of Computer Sci. and Engg., SRM University, Tamil Nadu, India
3 Mech. Engg. Dept., Dr. M.G.R Educational and Research Institute, Tamilnadu, India
 

   Subscribe/Renew Journal


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.
User
Subscription Login to verify subscription
Notifications
Font Size

  • 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.

Abstract Views: 500

PDF Views: 161




  • Warranty Cost Estimation using K-Means Cluster Analysis for Automobile Industry:Technical Note

Abstract Views: 500  |  PDF Views: 161

Authors

R. Srinivasan
Mech. Engg. Dept., Dr. M.G.R Educational and Research Institute, Tamil Nadu, India
S. Prasanna Devi
Dept. of Computer Sci. and Engg., SRM University, Tamil Nadu, India
S. Manivannan
Mech. Engg. Dept., Dr. M.G.R Educational and Research Institute, Tamil Nadu, India
N. Ethiraj
Mech. Engg. Dept., Dr. M.G.R Educational and Research Institute, Tamilnadu, India

Abstract


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.

References





DOI: https://doi.org/10.4273/ijvss.11.1.08