This paper presents a novel method of field reliability prediction considering environment variation and product individual dispersion. Wiener diffusion process with drift was used for degradation modeling and a link function which presents degradation rate is introduced to model the impact of varied environment and individual dispersion. Gamma, transformed-Gamma (T-Gamma) and Normal distribution with different parameters are employed to model rightskewed, left-skewed and symmetric stress distribution in the study case. Results show obvious difference in reliability, failure intensity and failure rate compared to constant stress situation and each other. It indicates that properly modeled (proper distribution type and parameters) environmental stress is the fundamental of varied environment oriented reliability prediction. In a linear drift degradation process and Arrheniustype link function situation, it is reasonable not concerning about product individual dispersion because the impact is barely small, while other situations can be studied in the same way proposed in this present paper. I TRODUCTIOReliability testing is carried out to study how environmental conditions affect the product performance. But these tests are usually conducted at a certain virtual environmental stress level whereas the field environment is highly varied from the virtual environment. However, there is little understanding on how field environment affect product reliability. Most of previous works of field reliability prediction treat environment stress as a constant at the average level [1] and may fail to give accurate prediction when the field environment is given. Meeker and Escobar [2] proposed a general framework using laboratory test results to predict field performance in a highly varied environment. Eghbali [3] proposed a proportional degradation hazard model which was employed by Wang [4] to extend existing degradation model capabilities to field systems. Vaca-Trigo and Meeker [5] provided a statistical model for linking field and laboratory exposure results for a model coating. Meeker and Escobar[6] developed a model and method for combining accelerated test data and field data to predict the failure time distribution for a future improved product operating in the same environment conditions. However, these works cannot handle the situation that the environment can be modeled by a statistical distribution. Then Liu and Ma [7] proposed a method to conduct field reliability prediction, employing Wiener diffusion process with drift to model the degradation process and an Arrhenius-type link function with Gamma distribution to describe temperature variation.However, all these works did not discuss how the type and parameters of environment distribution affect reliability, failure intensity and failure rate. Moreover, each product has different degradation rate due to individual dispersion caused by random factors in material preparation and manufacturing process. It is also reasonable to be considered in reliability prediction.I...
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