Prognostics and health management of electronics : (Record no. 69159)

000 -LEADER
fixed length control field 06488cam a2200625 i 4500
001 - CONTROL NUMBER
control field on1043051822
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220711203537.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 180702s2018 nju ob 001 0 eng
019 ## -
-- 1048895928
-- 1049605644
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781119515357
-- (ePub)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1119515351
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781119515302
-- (Adobe PDF)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1119515300
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781119515326
-- (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1119515327
-- (electronic bk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
-- (hardcover)
082 00 - CLASSIFICATION NUMBER
Call Number 621.381028/8
245 00 - TITLE STATEMENT
Title Prognostics and health management of electronics :
Sub Title fundamentals, machine learning, and internet of things /
250 ## - EDITION STATEMENT
Edition statement Second edition.
300 ## - PHYSICAL DESCRIPTION
Number of Pages 1 online resource
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Cover; Title Page; Copyright; About the Editors; Contents; List of Contributors; Preface; About the Contributors; Acknowledgment; List of Abbreviations; Chapter 1 Introduction to PHM; 1.1 Reliability and Prognostics; 1.2 PHM for Electronics; 1.3 PHM Approaches; 1.3.1 PoF-Based Approach; 1.3.1.1 Failure Modes, Mechanisms, and Effects Analysis (FMMEA); 1.3.1.2 Life-Cycle Load Monitoring; 1.3.1.3 Data Reduction and Load Feature Extraction; 1.3.1.4 Data Assessment and Remaining Life Calculation; 1.3.1.5 Uncertainty Implementation and Assessment; 1.3.2 Canaries; 1.3.3 Data-Driven Approach.
505 8# - FORMATTED CONTENTS NOTE
Remark 2 1.3.3.1 Monitoring and Reasoning of Failure Precursors1.3.3.2 Data Analytics and Machine Learning; 1.3.4 Fusion Approach; 1.4 Implementation of PHM in a System of Systems; 1.5 PHM in the Internet of Things (IoT) Era; 1.5.1 IoT-Enabled PHM Applications: Manufacturing; 1.5.2 IoT-Enabled PHM Applications: Energy Generation; 1.5.3 IoT-Enabled PHM Applications: Transportation and Logistics; 1.5.4 IoT-Enabled PHM Applications: Automobiles; 1.5.5 IoT-Enabled PHM Applications: Medical Consumer Products; 1.5.6 IoT-Enabled PHM Applications: Warranty Services.
505 8# - FORMATTED CONTENTS NOTE
Remark 2 1.5.7 IoT-Enabled PHM Applications: Robotics1.6 Summary; References; Chapter 2 Sensor Systems for PHM; 2.1 Sensor and Sensing Principles; 2.1.1 Thermal Sensors; 2.1.2 Electrical Sensors; 2.1.3 Mechanical Sensors; 2.1.4 Chemical Sensors; 2.1.5 Humidity Sensors; 2.1.6 Biosensors; 2.1.7 Optical Sensors; 2.1.8 Magnetic Sensors; 2.2 Sensor Systems for PHM; 2.2.1 Parameters to be Monitored; 2.2.2 Sensor System Performance; 2.2.3 Physical Attributes of Sensor Systems; 2.2.4 Functional Attributes of Sensor Systems; 2.2.4.1 Onboard Power and Power Management.
505 8# - FORMATTED CONTENTS NOTE
Remark 2 2.2.4.2 Onboard Memory and Memory Management2.2.4.3 Programmable Sampling Mode and Sampling Rate; 2.2.4.4 Signal Processing Software; 2.2.4.5 Fast and Convenient Data Transmission; 2.2.5 Reliability; 2.2.6 Availability; 2.2.7 Cost; 2.3 Sensor Selection; 2.4 Examples of Sensor Systems for PHM Implementation; 2.5 Emerging Trends in Sensor Technology for PHM; References; Chapter 3 Physics-of-Failure Approach to PHM; 3.1 PoF-Based PHM Methodology; 3.2 Hardware Configuration; 3.3 Loads; 3.4 Failure Modes, Mechanisms, and Effects Analysis (FMMEA); 3.4.1 Examples of FMMEA for Electronic Devices.
505 8# - FORMATTED CONTENTS NOTE
Remark 2 3.5 Stress Analysis3.6 Reliability Assessment and Remaining-Life Predictions; 3.7 Outputs from PoF-Based PHM; 3.8 Caution and Concerns in the Use of PoF-Based PHM; 3.9 Combining PoF with Data-Driven Prognosis; References; Chapter 4 Machine Learning: Fundamentals; 4.1 Types of Machine Learning; 4.1.1 Supervised, Unsupervised, Semi-Supervised, and Reinforcement Learning; 4.1.2 Batch and Online Learning; 4.1.3 Instance-Based and Model-Based Learning; 4.2 Probability Theory in Machine Learning: Fundamentals; 4.2.1 Probability Space and Random Variables.
520 ## - SUMMARY, ETC.
Summary, etc AN INDISPENSABLE GUIDE FOR ENGINEERS AND DATA SCIENTISTS IN DESIGN, TESTING, OPERATION, MANUFACTURING, AND MAINTENANCE A road map to the current challenges and available opportunities for the research and development of Prognostics and Health Management "PHM", this important work covers all areas of electronics and explains how to: . assess methods for damage estimation of components and systems due to field loading conditions. assess the cost and benefits of prognostic implementations. develop novel methods for in situ monitoring of products and systems in actual life-cycle conditions. enable condition-based "predictive" maintenance. increase system availability through an extension of maintenance cycles and/or timely repair actions. obtain knowledge of load history for future design, qualification, and root cause analysis. reduce the occurrence of no fault found "NFF". subtract life-cycle costs of equipment from reduction in inspection costs, downtime, and inventory Prognostics and Health Management of Electronics also explains how to understand statistical techniques and machine learning methods used for diagnostics and prognostics. Using this valuable resource, electrical engineers, data scientists, and design engineers will be able to fully grasp the synergy between IoT, machine learning, and risk assessment.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
General subdivision Maintenance and repair.
650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1
General subdivision Mechanical.
650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1
General subdivision Maintenance and repair.
700 1# - AUTHOR 2
Author 2 Pecht, Michael,
700 1# - AUTHOR 2
Author 2 Kang, Myeongsu,
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1002/9781119515326
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Hoboken, NJ :
-- John Wiley & Sons,
-- 2018.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
588 0# -
-- Print version record and CIP data provided by publisher.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Electronic systems
650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1
-- TECHNOLOGY & ENGINEERING
650 #7 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Electronic systems
-- (OCoLC)fst00907488
994 ## -
-- C0
-- DG1

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