AI Techniques for Reliability Prediction for Electronic Components. This item is unavailable.AI Techniques for Reliability Prediction for Electronic Components

In the industry of manufacturing and design, one major constraint has been enhancing operating performance using less time. As technology continues to advance, manufacturers are looking for better methods in predicting the condition and residual lifetime of electronic devices in order to save repair costs and their reputation. Intelligent systems are a solution for predicting the reliability of these components; however, there is a lack of research on the advancements of this smart technology within the manufacturing industry.

AI Techniques for Reliability Prediction for Electronic Components provides emerging research exploring the theoretical and practical aspects of prediction methods using artificial intelligence and machine learning in the manufacturing field. Featuring coverage on a broad range of topics such as data collection, fault tolerance, and health prognostics, this book is ideally designed for reliability engineers, electronic engineers, researchers, scientists, students, and faculty members seeking current research on the advancement of reliability analysis using AI.

Cherry Bhargava is working as an associate professor and head, VLSI domain, School of Electrical and Electronics Engineering at Lovely Professional University, Punjab, India. She has more than 14 years of teaching and research experience. She is PhD (ECE), IKGPTU, M.Tech (VLSI Design & CAD) Thapar University and B.Tech (Electronics and Instrumentation) from Kurukshetra University. She is GATE qualified with All India Rank 428. She has authored about 50 technical research papers in SCI, Scopus indexed quality journals and national/international conferences. She has seven books related to reliability, artificial intelligence and digital electronics to her credit. She has registered three copyrights and filed two patents. She is recipient of various national and international awards for being outstanding faculty in engineering and excellent researcher. She is an active reviewer and editorial member of various prominent SCI and Scopus indexed journals. She is a lifetime member of IET, IAENG, NSPE, IAOP, WASET and reliability research group. Her area of expertise includes reliability of electronic systems, digital electronics, VLSI design, artificial intelligence and related technologies.