Reliability Data Analysis for Designed Experiments

Product reliability is an important characteristic for all manufacturers, engineers and consumers. Industrial statisticians have been planning experiments for years to improve product quality and reliability. However, rarely do experts in the field of reliability have expertise in design of experiments (DOE) and the implications that experimental protocol have on data analysis. Additionally, statisticians who focus on DOE rarely work with reliability data. This talk is an attempt to bridge that divide. We provide a new analysis technique for reliability data from designed experiments. The technique is illustrated on a popular reliability data set. This paper discusses implications of using previous analysis methods versus our new approach to the analysis problem.