Abstract

Using data from a simple step-stress accelerated life test procedure, a non-parametric proportional hazards model is proposed for obtaining upper confidence bounds for the cumulative failure probability of a product under normal use conditions. The approach is non-parametric in the sense that most of the functions involved in the model do not assume any specific forms, except for certain verifiable conditions. Test statistics are introduced to verify assumptions about the model and to test the goodness of fit of the proposed model to the data. A numerical example, using data simulated from the lifetime distribution of an existing parametric study on metal-oxide semiconductor capacitors, is used to illustrate the proposed methods. Discussions on how to determine the optimal stress levels and sample size are also given.

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