Reliability Data Analysis for Life Test Experiments with Subsampling

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. The standard analysis techniques currently in use for reliability data assume a completely randomized design. However, analysis methodologies for experimental designs more complex than completely randomized designs have not been a focus of the reliability field. We provide a new, yet simple, analysis technique for reliability data from designed experiments containing subsampling. 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.