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Webinar: Analyzing ALT Data by Dr. Rong Pan
Analyzing ALT Data by Dr. Rong Pan
Join us for our next webinar! September 13, 2022 8:30-11:30 am Pacific time (California) Cost $300 per person Group discounts available! Please note, this webinar will be recorded. If the time is not convenient for you, this webinar recording link can be purchased to view at your leisure. Contact us for details.
Register here and pass on to your co-workers!
Course Description: Accelerated life testing (ALT) is a direct approach to obtain product failure time information and is widely employed in the product development and reliability improvement process. Companies may use ALTs for multiple purposes such as quantifying the failure time acceleration factor for specific environmental stress variable, validating a stress-lifetime relationship, and predicting some reliability measures under normal use condition, etc. In this webinar, we will first give a thorough presentation of different ALT plans and the varying data forms generated from ALTs. In order to draw valid conclusions from ALT data, proper statistical analysis methods must be chosen. Therefore, we will study both lifetime distribution models and lifetime regression models and demonstrate their usefulness in ALT data analysis. We will show the impact of failure time censoring on distribution parameter estimation and how to select a good regression model from both the physics-of-failure and goodness-of-fit perspectives. This webinar will also provide hands-on exercises using JMP and R. All software codes and step-by-step instructions will be provided to attendees before the webinar.
Instructor: Dr. Rong Pan is an Associate Professor of Industrial Engineering and Data Science in the School of Computing and Augmented Intelligence at Arizona State University. He is the program chair of the Data Science, Analytics and Engineering PhD program at ASU. His research interests include failure time data analysis, design of experiments, multivariate statistical process control, time series analysis, and computational Bayesian methods. He has over 20 years’ experience in teaching and research in the areas of statistical methods for reliability modeling and data analysis. His research has been supported by NSF, Arizona Science Foundation, Air Force Research Lab, etc. He has published over 90 journal papers and 60+ refereed conference papers. He was the recipient of the Stan Ofsthum Award in 2008, 2011 and 2018 and William A. Golomski Award in 2015 and 2020. His papers won the Best Reliability Paper Award of Quality Engineering in 2012 and 2013. Dr. Pan is a senior member of ASQ, IIE and IEEE, and a lifetime member of SRE. He serves on the editorial boards of Journal of Quality Technology and Quality Engineering.
Cost $300 per person, if you have five or more the cost is $270 per person
Time 8:30 – 11:30 am Pacific (California)
After registering, you will receive a confirmation email containing information about joining the webinar.