报告人：亚利桑那州立大学 Rong Pan 副教授
More and more often reliability engineers are encountering “big data”. They could be field data from warranty claims and maintenance records, sensor data from environmental and operating condition monitoring devices, or performance data from IoT technologies. In this talk I will share some personal experience of dealing with reliability big data from the data analytics perspective. I will discuss the impact of data volume, data variety and data veracity on statistical modeling and inferences, as well as some exciting research opportunities opening up to the researchers who are interested in the areas of quality and reliability improvement.
Dr. Rong Pan is an Associate Professor of Industrial Engineering in the School of Computing, Informatics, and Decision Systems Engineering at Arizona State University. His research interests include failure time analysis, design of experiments, time series analysis, multivariate statistics and computational Bayesian methods. He has published over 70 journal papers and 50+ refereed conference papers. He was the recipient of Stan Ofsthum Award in 2008, 2011 and 2018, and William A. Golomski Award in 2015. His papers won the Best Reliability Paper Award of Quality Engineering in 2012 and 2013. He serves on the editorial boards of Journal of Quality Technology and Quality Engineering.