Chapter 1 provides a basic understanding of PHM and the techniques being developed to enable prognostics for electronic products and systems. Chapter 2 presents the state of the art in sensor systems for in-situ health and usage monitoring. Chapter 3 discusses the various models and algorithms that can be utilized for PHM. Chapter 4 presents the challenges and opportunities for research and development in PHM of electronics.

Michael G. Pecht, PHD, has an MS in electrical engineering and a PhD in engineering mechanics. He is a Professional Engineer, an IEEE Fellow, an ASME Fellow, and an IMAPS Fellow. He was editor of the IEEE Transactions on Reliability for eight years. He is now editor for Microelectronics Reliability. He is a Chair Professor and the Director of the CALCE Electronic Products and Systems Center at the University of Maryland. He has written more than 20 books on electronic products development and reliability, and over 400 technical articles. In 2008, he was awarded the highest reliability honor, the IEEE Reliability Society's Lifetime Achievement Award.

Preface	p. ix
Acknowledgements	p. xi
Acronyms	p. xv
Introduction	p. 1
Reliability and Prognostics	p. 1
PHM for Electronics	p. 3
PHM Concepts and Methods	p. 6
Fuses and Canaries	p. 7
Monitoring and Reasoning of Failure Precursors	p. 9
Monitoring Environmental and Usage Profiles for Damage Modeling	p. 13
Implementation of PHM for System of Systems	p. 18
Summary	p. 19
Sensor Systems for PHM	p. 25
Sensor and Sensing Principles	p. 25
Thermal Sensors	p. 26
Electrical Sensors	p. 27
Mechanical Sensors	p. 28
Humidity Sensors	p. 28
Biosensors	p. 29
Chemical Sensors	p. 29
Optical Sensors	p. 30
Magnetic Sensors	p. 31
Sensor Systems for PHM	p. 32
Parameters to Be Monitored	p. 33
Sensor System Performance	p. 33
Physical Attributes of Sensor Systems	p. 34
Functional Attributes of Sensor Systems	p. 34
Cost	p. 38
Reliability	p. 38
Availability	p. 38
Sensor Selection	p. 38
Examples of Sensor Systems for PHM Implementation	p. 41
Emerging Trends in Sensor Technology for PHM	p. 44
Data-Driven Approaches for PHM	p. 47
Introduction	p. 47
Parametric Statistical Methods	p. 48
Likelihood Ratio Test	p. 49
Maximum Likelihood Estimation	p. 50
Neyman-Pearson Criterion	p. 50
Expectation Maximization	p. 51
Minimum Mean Square Error Estimation	p. 51
Maximum A Posteriori Estimation	p. 51
Rao-Blackwell Estimation	p. 52
Cramer-Rao Lower Bound	p. 52
Nonparametric Statistical Methods	p. 52
Nearest Neighbor-Based Classification	p. 52
Parzen Window (or Kernel Density Estimation)	p. 53
Wilcoxon Rank-Sum Test	p. 54
Kolmogorov-Smirnov Test	p. 54
Chi Square Test	p. 54
Machine Learning Techniques	p. 55
Supervised Classification	p. 57
Discriminative Approach	p. 57
Generative Approach	p. 61
Unsupervised Classification	p. 63
Discriminative Approach	p. 63
Generative Approach	p. 65
Summary	p. 67
Physics-of-Failure Approach to PHM	p. 73
PoF-Based PHM Methodology	p. 73
Hardware Configuration	p. 74
Loads	p. 74
Failure Modes, Mechanisms, and Effects Analysis	p. 75
Stress Analysis	p. 78
Reliability Assessment and Remaining-Life Predictions	p. 79
Outputs from PoF Based PHM	p. 82
The Economics of PHM	p. 85
Return on Investment	p. 85
PHM ROI Analyses	p. 86
Financial Costs	p. 88
PHM Cost-Modeling Terminology and Definitions	p. 88
PHM Implementation Costs	p. 89
Nonrecurring Costs	p. 90
Recurring Costs	p. 90
Infrastructure Costs	p. 91
Nonmonetary Considerations and Maintenance Culture	p. 91
Cost Avoidance	p. 93
Maintenance Planning Cost Avoidance	p. 94
Discrete Event Simulation Maintenance Planning Model	p. 95
Fixed-Schedule Maintenance Interval	p. 96
Precursor to Failure Monitoring	p. 96
LRU-Independent Methods	p. 97
Discrete Event Simulation Implementation Details	p. 99
Operational Profile	p. 100
Example PHM Cost Analysis	p. 101
Single-Socket Model Results	p. 102
Multiple-Socket Model Results	p. 104
Example Business Case Construction	p. 108
Summary	p. 114
PHM Roadmap: Challenges and Opportunities	p. 119
Introduction	p. 119
Roadmap Classifications	p. 120
PHM: Component Level	p. 121
PHM for Integrated Circuits and Gate Devices	p. 121
High-Power Switching Electronics	p. 122
Built-in Prognostics for Components and Circuit Boards	p. 123
Electronics/Electro-Optical Prognostics for Tactical Sensor Systems	p. 123
Interconnect Prognostics	p. 124
PHM as Mitigation of Reliability Risks	p. 124
PHM in Supply Chain Management and Product Maintenance	p. 125
PHM at System Level	p. 125
Legacy Systems	p. 126
Environmental and Operational Monitoring	p. 126
LRU to Device Level	p. 126
Dynamic Reconfiguration	p. 126
System Power Management and PHM	p. 127
PHM as Knowledge Infrastructure for System Development	p. 127
Prognostics for Software	p. 127
Methodology Development	p. 129
Best Algorithms	p. 130
Approaches to Training	p. 130
Verification and Validation	p. 131
Long-Term PHM Studies	p. 131
Nontechnical Barriers	p. 131
Cost, ROI, Business Case Development	p. 131
Liability and Litigation	p. 132
Role of Standards Organizations	p. 133
Commercially Available Sensor Systems for PHM	p. 135
PHM in Industry, Academia, and Government	p. 167
Journals and Conference Proceedings Related to PHM	p. 307
Index	p. 309
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Prognostics and Health Management of Electronics

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