Analyzing Censored Failure Time Data by Dr. Rong Pan 2 hours Cost $200 per person Group discounts available!
From reliability tests and field observations, it is common to encounter incomplete failure time information. In general, the exact failure time may not be obtained, but some partial information, such as survival time or the interval times between which the product fails, is available. Analyzing censored failure time data is an essential skill that a reliability engineer should master. The ASQ’s Body of Knowledge of Certified Reliability Engineer demands 27 questions in the area of probability and statistics for reliability and 24 questions in reliability testing. Together, they consist of the biggest block of questions in the certification test.
In this webinar we present the techniques of how to recognize and classify censored failure time data, and how to analyze them in both nonparametric and parametric ways. In addition, based on the properties of reliability estimates, we can properly compare reliabilities of products from two and more manufacturers/suppliers, and construct statistically efficient tests to demonstrate reliability. As nowadays most data analysis can be performed by computer, we will show the reliability data analysis on multiple examples using Minitab® and JMP® , as well as some Excel® templates that are customized for specific reliability analysis tasks.
Rong Pan is an Associate Professor of Industrial Engineering in the School of Computing, Informatics, and Decision Systems Engineering at Arizona State University. He received his Ph.D. degree in Industrial Engineering from Penn State University in 2002. His research interests include failure time data analysis, system reliability, design of experiments, multivariate statistical process control, time series analysis, and computational Bayesian methods. His research has been supported by NSF, DOE, Arizona Science Foundation, Air Force Research Lab, etc. He has published over 50 peer-reviewed journal papers and many more refereed conference papers. He was the recipient of 2008 and 2011 Stan Ofsthun Awards and 2015 William A. Golomski Award. His papers won 2012 and 2013 Best Reliability Paper Awards in Quality Engineering and 2017 SPES award by ASA. He is a senior member of ASQ, IIE and IEEE, and a member of SRE and INFORMS.
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