The reliability characteristics of automobile components depend on factors or covariatessuch as the automobile operating environment (e.g. temperature, rainfall, humidity, etc.), usage conditions, manufacturing periods, types of automobiles which use the components, etc. In recent years, many automotive manufacturing companies utilize warranty database as a very rich source of field reliability data that provide valuable information on such covariates for feedback to new product development systems on product performance in actual usage conditions. In warranty database, the information on those covariates are known for the components which fail within the warranty period and are unknown for the censored components. This article considers covariates associated with some reliability-related factors and presents a Weibull regression model for the lifetime of the component as a function of such covariates. The EM algorithm is applied to obtain the ML estimates of the parameters of the model because of incomplete information on covariates. An example based on real field data of automobile component is given to illustrate the use of the proposed method.
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