Models for Optimization of Production Environmental Stress Testing on Electronic Circuit Packs

Abstract

The problem of optimizing accelerated production testing is a pressing one in most electronic manufacturing facilities. Yet, practical models are scarce in the literature, especially for testing high volumes of electronic circuit packs in failure-accelerating environments. In this paper, we develop both a log-linear and linear model, based initially on the Weibull distribution. The models developed are suitable for modeling accelerated production testing data from a temperature-cycled environment. The model is "piecewise" in that the failures in each discrete "piece" of the temperature cycle are modeled as if the testing was in parallel rather than sequential mode. An extra covariate is introduced to indicate age at the start of each piece. The failures in a piece then depend on the stress in the piece itself and the time elapsed to the start of the piece. This last dependence captures the influence of reliability growth and has the result of providing * Centre for Telecommunications Value-Chain Research. 555 Int. J. Rel. Qual. Saf. Eng. 2008.15:555-579. Downloaded from www.worldscientific.com by RUTGERS UNIVERSITY on 04/04/15. For personal use only. 556 T. Joyce et al.an alternative linear model to the log-linear one. The paper demonstrates a simpler use of Poisson regression. An application, using actual production data, is described. Uses of the Loglogistic, Logistic, Lognormal and Normal distributions are also illustrated.

Stress test optimization using an integrated production test and field reliability model

“…Honari et al 30 developed a method of optimizing the test time using field and test data. A piecewise regression model was applied by Joyce et al 31 to temperature cycling test in order to optimize the EST.…”