Application of Generalized Linear Models for Optimizing Production Stress Testing

This paper uses Generalized Linear Modeling (GLM) to investigate the effects of the production and EST test variables on the population under test. Both the number of units rejected and the time to failure can be modeled as a regression function of covariates representative of the test environment. The field reliability function is written as a product of the unconditional reliability in each segment of the test profile such as dwell, ramp, etc. 

The next step is to apply the result of the temperature cycle EST GLM to a mathematical cost model. This cost model includes both the test cost and the warranty and compensation costs of the early field failures. The optimum test regime and number of cycles, which minimizes the total cost is determined by combining the GLM and the cost model. In this way the production test regime can be optimized in terms of field reliability/test cost trade-off.