Experiences and Pitfalls in Reliability Data Analysis and Test Planning
William Q. Meeker, Iowa State University
Tuesday, June 9, 2015
Room 2431 (Executive Classroom)
Reliability assurance processes in manufacturing industries require data-driven information for making product-design decisions. Life tests, accelerated life tests, and accelerated degradation tests are commonly used to collect reliability data. Data from products in the field provide another important source of useful reliability information. These reliability studies typically yield data that are censored and/or truncated, require the use of less familiar distributions like the Weibull, the lognormal, and the gamma, and call for inferences that involve extrapolation. This short course will present and discuss the analyses of many different life data analysis applications in the area of product reliability and materials evaluation. The analyses illustrate the use of a mix of proven traditional techniques, enhanced and brought up to date with modern computer-based methodology. Methods used in the analyses include nonparametric estimation, probability plotting, maximum likelihood estimation of parametric models, analysis of data with multiple failure modes, likelihood-based confidence intervals, acceleration models, accelerated life testing, Bayesian methods, accelerated degradation testing, and the analysis of recurrence data from repairable systems.