Prognostics and Health Management of electronics available now
Prognostics and Health Management of Electronics: Fundamentals, Machine Learning, and the Internet of Things, by Prof. Michael Pecht and Dr. Myeongsu Kang, serves as a valuable resource to aid data scientists, engineers, and researchers in fully understanding and applying machine learning, the Internet of Things, and risk assessment to electronic components, products, and systems.
The first version of this book on PHM for electronic systems was written by Prof. Pecht in 2008. This new book of over 800 pages advances the research and practical applications of PHM conducted by the Center for Advanced Life Cycle Engineering’s (CALCE) Prognostics and Health Management (PHM) scholars. This work shows the newly developed methods for identifying anomalies and patterns within large data sets containing multiple parameters, both qualitative and quantitate, to develop real-time, reduced-order modeling for failure prediction. In addition, applications of PHM by CALCE industry partners are presented.
Table of Contents
1. Introduction to PHM
2. Sensor Systems for PHM
3. Physics-of-Failure Approach to PHM
4. Machine Learning: Fundamentals
5. Machine Learning: Data Pre-processing
6. Machine Learning for Anomaly Detection
7. Machine Learning: Diagnostics and Prognostics
8. Uncertainty Representation, Quantification, and Management in Prognostics
9. PHM Cost and Return on Investment
10. Valuation and Optimization of PHM-Enabled Maintenance Decisions
11. Health and Remaining Useful Life Estimation of Electronic Circuits
12. PHM-based Qualification of Electronics
13. PHM of Lithium-ion Batteries
14. PHM of Light-Emitting Diodes
15. PHM of Healthcare
16. PHM of Subsea Cables
17. Connected Vehicle Diagnostics and Prognostics
18. The Role of PHM at Commercial Airlines
19. PHM Software of Electronics
21. Predictive Maintenance in the IoT Era
22. Analysis of PHM Patents for Electronics
23. A PHM Roadmap for Electronics-Rich Systems
This book is currently available through Wiley and other retailers.
About the Authors
Michael G. Pecht, Ph.D., is Professor in Applied Mathematics, Statistics and Scientific Computation, as well as the George Dieter Chair Professor in Mechanical Engineering and at the University of Maryland, USA. He is the Founder and Director of the Center for Advanced Life Cycle Engineering (CALCE), which is currently funded by more than 150 leading electronics companies. Dr. Pecht has written more than 30 books and 700 technical articles and has 10 patents; his publications have been cited over 25,000 citations times.
The late Myeongsu Kang, Ph.D., worked as a Research Associate at the Center for Advanced Life Cycle Engineering (CALCE), University of Maryland, USA. He lent invaluable expertise in data analytics, machine learning, system modeling, and statistics for prognostics and systems health management. He authored/coauthored more than 60 publications in leading journals and conference proceedings.
Published April 8, 2019