TITLE: Research Issues on Life Data Analysis and Life Test Design
SPEAKER: Dr. Huairui (Harry) Guo
ABSTRACT:
ReliaSoft is a leading software company providing statistical analysis and project management tools for reliability and quality engineers. We have over 10 major software packages, such as Weibull++ for life data analysis, ALTA for accelerated life test design and analysis, and DOE++ for general experimental designs. In the development of our products, we have encountered many research issues and also received many requirements from our customers. In this talk, I will present several of these issues related to life data analysis and experimental design. I hope we can get input on these matters from experts like you. The possible research topics are:
1) How to adjust the bias of the maximum likelihood estimates (MLE) of the shape parameter of the Weibull distribution. The bias not only affects reliability prediction, it also affects the standard error of the estimated parameters, which can lead to incorrect conclusions from significance tests such as the likelihood ratio chi-squared test and the approximated standard normal test.
2) With censored data, it is sometimes impossible to get the MLE solution for a generalized linear model with the Weibull, exponential or lognormal distribution. How can we determine the existence of the MLE solution for a model by simply examining the data before calling the optimization routine to solve it?
3) Optimal designs have been widely used in Design of Experiments (DOE). However, with possible censored data from a life test, the traditional optimal design methods that utilize the information matrix cannot be applied directly. Research for designing optimal accelerated life tests with one and two stresses has been conducted, but we would like to explore the possibility of developing a general method for optimal life tests with any number of stresses. All of the current methods are based on the approximated Fisher information bounds (also called Wald confidence bounds); is it possible to design tests based on likelihood ratio bounds, which have been proved more accurate than the Fisher information bounds?
Bio: Dr. Huairui (Harry) Guo is the Director of Theoretical Development at ReliaSoft Corporation. He received his Ph.D. in Systems and Industrial Engineering from the University of Arizona. His research involves many areas of quality and reliability engineering, including SPC, ANOVA, DOE, repairable and non-repairable system reliability modeling, accelerated life and degradation testing, and warranty prediction. He has been invited to give presentations and seminars for NASA, ASQ, NREL and commercial companies. He has conducted consulting projects for companies from various industries, including renewable energy, oil and gas, automobile, medical devices and semi-conductors. As the leader of the theory team, he is deeply involved in the development of Weibull++, ALTA, DOE++, RGA, BlockSim, Lambda Predict and other products from ReliaSoft. Dr. Guo was the recipient of the Stan Ofsthun Award from the Society of Reliability Engineers (SRE) in 2008 and 2010. He also received the best paper award at the Institute of Industrial Engineers annual research conference in 2007.