AME Kececioglu Memorial Lecture: Michael Pecht

Abstract
The Internet of Things is not only permitting the sensing and control of numerous products and systems but enabling the collection of otherwise unattainable data. With the use of artificial intelligence methods, we can now use this data to assess the “health” (e.g. deviation or degradation) of a system from an expected normal operating condition, diagnose faults, to predict the future state of the system and forecast logistics actions, including maintenance and alternative mission profiles. This presentation discusses the artificial intelligence methods, gives examples of what companies have already implemented, and presents possibilities for the future.

Bio
Prof. Michael Pecht (35,000+ citations, 80+ H-Index) has a BS in Physics, an MS in Electrical Engineering, and an MS and Ph.D. in Engineering Mechanics from the University of Wisconsin. He is a professional engineer, an IEEE Fellow, a PHM Society Life Fellow, an ASME Fellow, an ASM Fellow, an SAE Fellow and an IMAPS Fellow. He served as editor-in-chief of IEEE Access for six years, as editor-in-chief of IEEE Transactions on Reliability for nine years, editor-in-chief of Microelectronics Reliability for sixteen years, and editor of Circuit World. He has also served on three U.S. National Academy of Science studies, two US Congressional investigations in automotive safety, and as an expert to the U.S. FDA. He is the director of CALCE (Center for Advanced Life Cycle Engineering) at the University of Maryland (UMd ), which is funded by over 150 of the world’s leading electronics companies at more than US$6M/year. He is also a professor in Applied Mathematics at UMd. In 2008, he was awarded the highest reliability honor, the IEEE Reliability Society’s Lifetime Achievement Award. In 2010, he received the IEEE Exceptional Technical Achievement Award for his innovations in the area of prognostics and systems health management.