Prognostics and Health Management of Electronics

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  • Format: Hardcover
  • Copyright: 2008-09-02
  • Publisher: Wiley-Interscience

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Supplemental Materials

What is included with this book?


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.

Author Biography

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.

Table of Contents

Prefacep. ix
Acknowledgementsp. xi
Acronymsp. xv
Introductionp. 1
Reliability and Prognosticsp. 1
PHM for Electronicsp. 3
PHM Concepts and Methodsp. 6
Fuses and Canariesp. 7
Monitoring and Reasoning of Failure Precursorsp. 9
Monitoring Environmental and Usage Profiles for Damage Modelingp. 13
Implementation of PHM for System of Systemsp. 18
Summaryp. 19
Sensor Systems for PHMp. 25
Sensor and Sensing Principlesp. 25
Thermal Sensorsp. 26
Electrical Sensorsp. 27
Mechanical Sensorsp. 28
Humidity Sensorsp. 28
Biosensorsp. 29
Chemical Sensorsp. 29
Optical Sensorsp. 30
Magnetic Sensorsp. 31
Sensor Systems for PHMp. 32
Parameters to Be Monitoredp. 33
Sensor System Performancep. 33
Physical Attributes of Sensor Systemsp. 34
Functional Attributes of Sensor Systemsp. 34
Costp. 38
Reliabilityp. 38
Availabilityp. 38
Sensor Selectionp. 38
Examples of Sensor Systems for PHM Implementationp. 41
Emerging Trends in Sensor Technology for PHMp. 44
Data-Driven Approaches for PHMp. 47
Introductionp. 47
Parametric Statistical Methodsp. 48
Likelihood Ratio Testp. 49
Maximum Likelihood Estimationp. 50
Neyman-Pearson Criterionp. 50
Expectation Maximizationp. 51
Minimum Mean Square Error Estimationp. 51
Maximum A Posteriori Estimationp. 51
Rao-Blackwell Estimationp. 52
Cramer-Rao Lower Boundp. 52
Nonparametric Statistical Methodsp. 52
Nearest Neighbor-Based Classificationp. 52
Parzen Window (or Kernel Density Estimation)p. 53
Wilcoxon Rank-Sum Testp. 54
Kolmogorov-Smirnov Testp. 54
Chi Square Testp. 54
Machine Learning Techniquesp. 55
Supervised Classificationp. 57
Discriminative Approachp. 57
Generative Approachp. 61
Unsupervised Classificationp. 63
Discriminative Approachp. 63
Generative Approachp. 65
Summaryp. 67
Physics-of-Failure Approach to PHMp. 73
PoF-Based PHM Methodologyp. 73
Hardware Configurationp. 74
Loadsp. 74
Failure Modes, Mechanisms, and Effects Analysisp. 75
Stress Analysisp. 78
Reliability Assessment and Remaining-Life Predictionsp. 79
Outputs from PoF Based PHMp. 82
The Economics of PHMp. 85
Return on Investmentp. 85
PHM ROI Analysesp. 86
Financial Costsp. 88
PHM Cost-Modeling Terminology and Definitionsp. 88
PHM Implementation Costsp. 89
Nonrecurring Costsp. 90
Recurring Costsp. 90
Infrastructure Costsp. 91
Nonmonetary Considerations and Maintenance Culturep. 91
Cost Avoidancep. 93
Maintenance Planning Cost Avoidancep. 94
Discrete Event Simulation Maintenance Planning Modelp. 95
Fixed-Schedule Maintenance Intervalp. 96
Precursor to Failure Monitoringp. 96
LRU-Independent Methodsp. 97
Discrete Event Simulation Implementation Detailsp. 99
Operational Profilep. 100
Example PHM Cost Analysisp. 101
Single-Socket Model Resultsp. 102
Multiple-Socket Model Resultsp. 104
Example Business Case Constructionp. 108
Summaryp. 114
PHM Roadmap: Challenges and Opportunitiesp. 119
Introductionp. 119
Roadmap Classificationsp. 120
PHM: Component Levelp. 121
PHM for Integrated Circuits and Gate Devicesp. 121
High-Power Switching Electronicsp. 122
Built-in Prognostics for Components and Circuit Boardsp. 123
Electronics/Electro-Optical Prognostics for Tactical Sensor Systemsp. 123
Interconnect Prognosticsp. 124
PHM as Mitigation of Reliability Risksp. 124
PHM in Supply Chain Management and Product Maintenancep. 125
PHM at System Levelp. 125
Legacy Systemsp. 126
Environmental and Operational Monitoringp. 126
LRU to Device Levelp. 126
Dynamic Reconfigurationp. 126
System Power Management and PHMp. 127
PHM as Knowledge Infrastructure for System Developmentp. 127
Prognostics for Softwarep. 127
Methodology Developmentp. 129
Best Algorithmsp. 130
Approaches to Trainingp. 130
Verification and Validationp. 131
Long-Term PHM Studiesp. 131
Nontechnical Barriersp. 131
Cost, ROI, Business Case Developmentp. 131
Liability and Litigationp. 132
Role of Standards Organizationsp. 133
Commercially Available Sensor Systems for PHMp. 135
PHM in Industry, Academia, and Governmentp. 167
Journals and Conference Proceedings Related to PHMp. 307
Indexp. 309
Table of Contents provided by Ingram. All Rights Reserved.

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