Prognostics and Health Management of Electronics
Recently, the field of prognostics for electronic products has received increased attention due to the potential to provide early warning of system failures, forecast maintenance as needed, and reduce life cycle costs. In response to the subject's growing interest among industry, government, and academic professionals, this book provides a road map to the current challenges and opportunities for research and development in Prognostics and Health Management (PHM).
The book begins with a review of PHM and the techniques being developed to enable a prognostics approach for electronic products and systems. building on this foundation, the book then presents the state of the art in sensor systems for in-situ health and usage monitoring. Next, it discusses the various models and algorithms that can be utilized in PHM. Finally, it concludes with a discussion of the opportunities in future research.
Readers can use the information in this book to:
Detect and isolate faults
Reduce the occurrence of No Fault Found (NFF)
Provide advanced warning of system failures
Enable condition-based (predictive) maintenance
Obtain knowledge of load history for future design, qualification, and root cause analysis
Increase system availability through an extension of maintenance cycles and/or timely repair actions
Subtract life cycle costs of equipment from reduction in inspection costs, down time, and inventory
Prognostics and Health Management of Electronics is an indispensable reference for electrical engineers in manufacturing, systems maintenance, and management, as well as design engineers in all areas of electronics.
Chapter 1: Introduction.
1.1 Reliability and Prognostics.
1.2 PHM for Electronics.
1.3 PHM Concepts and Methods.
1.4 Implementation of PHM for System-of-Systems.
Chapter 2: Sensor Systems for PHM.
2.1 Sensor and Sensing Principles.
2.2 Sensor System for PHM.
2.3 Sensor Selection.
2.4 Examples of Sensor Systems for PHM Implementation.
2.5 Emerging Trends in Sensor Technology for PHM.
Chapter 3: Data Driven Approaches for PHM.
3.2 Parametric Statistical Methods.
3.3 Non-Parametric Statistical Methods.
3.4 Machine Learning Techniques.
3.5 Supervised Classification.
3.6 Unsupervised Classification.
Chapter 4: Physics-of-Failure Approach to PHM.
4.1 The PoF based PHM methodology.
4.2 Hardware configuration.
4.4 Failure Modes, Mechanisms, and Effects Analysis.
4.5 Stress Analysis.
4.6 Reliability Assessment and Remaining Life Predictions.
4.7 Outputs from PoF based PHM.
Chapter 5: The Economics of PHM.
5.1 Return on Investment (ROI).
5.2 PHM Cost Modeling Terminology and Definitions.
5.3 PHM Implementation Costs.
5.4 Cost Avoidance.
5.5 Example PHM Cost Analysis.
Chapter 6: PHM Roadmap: Challenges and Opportunities.
6.2 Roadmap Classifications.
6.3 PHM at the System Level.
6.4 Methodology Development.
6.5 Non-technical Barriers.
Appendix. A Commercially Available Sensor Systems for PHM.
Appendix. B PHM in Industry, Academia and Government.
Appendix. C Journals and Conference Proceedings Related to PHM.
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