Predicting field reliability based on two-dimensional warranty data with learning effects

ABSTRACT Understanding the field reliability of a sold product is crucial to both managers and engineers for monitoring product quality and improving warranty service design. When practitioners model warranty data, they it often assume that the lifetimes of products manufactured on different days is homogeneously distributed (i.e., product reliability remains the same over time). Based on a two-dimensional warranty data set collected from an automobile manufacturer, we find that the reliability of products improves over time. A log-linear regression model on the failure rate of the products is proposed by considering the usage rate and manufacturing day as covariates. The maximum likelihood approach is used to estimate the parameters. The results show the existence of learning effects in reliability in the early stage of manufacturing. A learning-curve model is then used to predict the reliability of new items produced.

[1]  Kazuyuki Suzuki,et al.  Lifetime Estimation Using Only Failure Information From Warranty Database , 2009, IEEE Transactions on Reliability.

[2]  Yili Hong,et al.  Field-Failure Predictions Based on Failure-Time Data With Dynamic Covariate Information , 2013, Technometrics.

[3]  Gianpaolo Pulcini,et al.  A mixed-Weibull regression model for the analysis of automotive warranty data , 2005, Reliab. Eng. Syst. Saf..

[4]  Jeremy F. Shapiro,et al.  Optimal capacity expansion planning when there are learning effects , 1986 .

[5]  Anu G. Aggarwal and Sameer Anand P.K.Kapur.  A New Insight into Software Reliability Growth Modeling , 2009 .

[6]  Shaomin Wu,et al.  Warranty Claim Forecasting Based On Weighted Maximum Likelihood Estimation , 2012, Qual. Reliab. Eng. Int..

[7]  Shaomin Wu,et al.  Support vector regression for warranty claim forecasting , 2011, Eur. J. Oper. Res..

[8]  Emmanuel Yashchin.  Design and Implementation of Systems for Monitoring Lifetime Data , 2012 .

[9]  D. N. Prabhakar Murthy,et al.  Warranty Data Collection and Analysis , 2011 .

[10]  Wei Jiang,et al.  Likelihood-Based EWMA Charts for Monitoring Poisson Count Data With Time-Varying Sample Sizes , 2012 .

[11]  Andre Kleyner,et al.  A warranty forecasting model based on piecewise statistical distributions and stochastic simulation , 2005, Reliab. Eng. Syst. Saf..

[12]  Shaomin Wu,et al.  Warranty Data Analysis: A Review , 2012, Qual. Reliab. Eng. Int..

[13]  Joyce T. Chen.  MODELING LEARNING CURVE AND LEARNING COMPLEMENTARITY FOR RESOURCE ALLOCATION AND PRODUCTION SCHEDULING , 1983 .

[14]  Stefanka Chukova,et al.  Auto warranty and driving patterns , 2013, Reliab. Eng. Syst. Saf..

[15]  Shaomin Wu,et al.  Forecasting warranty claims considering dynamic over-dispersion , 2012 .

[16]  Nanua Singh,et al.  Forecasting automobile warranty performance in presence of ‘maturing data’ phenomena using multilayer perceptron neural network , 2005 .

[17]  Nanua Singh,et al.  Hazard rate estimation from incomplete and unclean warranty data , 2003, Reliab. Eng. Syst. Saf..

[18]  W. Nelson.  Statistical Methods for Reliability Data , 1998 .

[19]  D. Murthy,et al.  New product warranty: A literature review , 2002 .

[20]  Jirachai Buddhakulsomsiri,et al.  Association rule-generation algorithm for mining automotive warranty data , 2006 .

[21]  Jerald F. Lawless,et al.  Monitoring Warranty Claims With Cusums , 2012, Technometrics.

[22]  Emmanuel Yashchin.  Computational and Monte-Carlo Aspects of Systems for Monitoring Reliability Data , 2010, COMPSTAT.

[23]  Kim B. Clark,et al.  Behind the learning curve: a sketch of the learning process , 1991 .

[24]  Karl D. Majeske,et al.  A mixture model for automobile warranty data , 2003, Reliab. Eng. Syst. Saf..

[25]  J. Bert Keats,et al.  Statistical Methods for Reliability Data , 1999 .

[26]  William Q. Meeker,et al.  Early Detection of Reliability Problems Using Information From Warranty Databases , 2002, Technometrics.

[27]  Karl D. Majeske,et al.  A non-homogeneous Poisson process predictive model for automobile warranty claims , 2007, Reliab. Eng. Syst. Saf..