Analyzing accelerated degradation data by nonparametric regression

This paper presents a nonparametric regression accelerated life-stress (NPR ALS) model for accelerated degradation data wherein the data consist of gro ups of degrading curve data. In contrast to the usual parametric modeling, a nonparametric regression model relaxes assumptions on the form of the reg ression functions and lets data speak for themselves in searching for a sui table model for data. NPRALS assumes that various stress levels affect only the degradation rate, but not the shape of the degradation curve. An algor ithm is presented for estimating the components of NPRALS. By investigating the relationship between the acceleration factors and the stress levels, t he mean time to failure estimate of the product under the usual use conditi on is obtained. The procedure is applied to a set of data obtained from an accelerated degradation test for a light emitting diode product. The result s look very promising. The performance of NPRALS is further checked by a si mulated example and found satisfactory. We anticipate that NPRALS can be ap plied to other applications as well.