ôSurvival Regression: From Bio-Statistics to Engineering"
Reliability analysis of field data (for decision-making support of product recalls or warranty reserve estimation) typically involves modeling the survival probability as a function of the vehicle's time-inservice and mileage. In certain cases, however, a need arises toadditionally model the survival probability as a function of fixed and/or time-dependent covariates. Examples of the former may include "assembly plant", "production month", "days before sale", etc., and the latter could be "cumulative exposure before and after a TSB", "exposure to cold/hot season", etc. While survival regression models are quite popular in medical and pharmaceutical studies, their application in engineering data analysis is much less common. The purpose of the discussion is to show the practical benefits of using such models in automotive warranty data analysis.
Vasiliy Krivtsov is a Ford technical leader in reliability and statistical analysis. He holds M.S. and Ph.D. degrees in EE from Kharkov Polytechnic Institute, Ukraine and a Ph.D. in Reliability Engineering from the University of Maryland, USA. Dr. Krivtsov is the author and coľauthor of 50+ professional publications, including a book onReliability Engineering and Risk Analysis , 9 patented inventions and 3 Ford corporate secret inventions. He is an editor of the Elsveir's Reliability Engineering and System Safety journal and is a member of the IEEE Reliability Society. Prior to Ford, Krivtsov held the position of Associate Professor of Electrical Engineering in Ukraine, and that of a Research Affiliate at the University of Maryland Center for Reliability Engineering. Further information on Dr. Krivtsov's professional activity is available at www.krivtsov.net