TY - JOUR
T1 - Models for optimization of production environmental stress testing on electronic circuit packs
AU - Joyce, Toby
AU - Honari, Bahman
AU - Wilson, Simon
AU - Donovan, John
AU - Gaffney, Oonagh
PY - 2008/12
Y1 - 2008/12
N2 - 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 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.
AB - 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 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.
KW - Accelerated stress testing
KW - Generalized linear model
KW - Poisson regression
KW - Production environmental stress test
KW - Weibull regression
UR - http://www.scopus.com/inward/record.url?scp=64249132975&partnerID=8YFLogxK
U2 - 10.1142/S0218539308003222
DO - 10.1142/S0218539308003222
M3 - Article
AN - SCOPUS:64249132975
SN - 0218-5393
VL - 15
SP - 555
EP - 579
JO - International Journal of Reliability, Quality and Safety Engineering
JF - International Journal of Reliability, Quality and Safety Engineering
IS - 6
ER -