Reliability Data Analysis for Life Test Designed Experiments with Sub-Sampling
Article first published online: 20 JUN 2012
Copyright © 2012 John Wiley & Sons, Ltd.
Quality and Reliability Engineering International
Volume 29, Issue 4, pages 509–519, June 2013
How to Cite
Freeman, L. J. and Vining, G. G. (2013), Reliability Data Analysis for Life Test Designed Experiments with Sub-Sampling. Qual. Reliab. Engng. Int., 29: 509–519. doi: 10.1002/qre.1398
- Issue published online: 20 MAY 2013
- Article first published online: 20 JUN 2012
- Manuscript Accepted: 23 JAN 2012
- Manuscript Received: 27 DEC 2011
- lifetime data;
- nonlinear mixed models;
- random effect;
- Weibull distribution
The ability to model lifetime data from life test experiments is of paramount importance to all manufacturers, engineers and consumers. The Weibull distribution is commonly used to model the data from life tests. Standard Weibull analysis assume completely randomized designs. However, not all life test experiments come from completely randomized designs. Experiments involving sub-sampling require a method for properly modeling the data. We provide a Weibull nonlinear mixed models (NLLMs) methodology for incorporating random effects in the analysis. We apply this methodology to a reliability life test on glass capacitors. We compare the NLLMs methodology to other available methods for incorporating random effects in reliability analysis. A simulation study reveals the method proposed in this paper is robust to both model misspecification and increasing levels of variance on the random effect. Copyright © 2012 John Wiley & Sons, Ltd.