How to minimize the global problem of e-waste Key Features Explore core concepts of Reliability Analysis, various smart models, different electronic components, and practical use of MATLAB. Cutting edge coverage on building intelligent systems for reliability analysis. Includes numerous techniques and methods to identify failure and reliability parameters. Description Intelligent Reliability Analysis using MATLAB and AI explains a roadmap to analyze and predict various electronic components future life and performance reliability. Deeply narrated and authored by reliability experts, this book empowers the reader to deepen their understanding of reliability identification, its significance, preventive measures, and various techniques. The book teaches how to predict the residual lifetime of active and passive components using an interesting use case on electronic waste. The book will demonstrate how the capacity of re-usability of electronic components can benefit the consumer to reuse the same component, with the confidence of successful operations. It lists key attributes and ways to design experiments using Taguchis approach, based on various acceleration factors. This book makes it easier for readers to understand reliability modeling of active and passive components using the Artificial Neural Network, Fuzzy Logic, Adaptive Neuro-Fuzzy Inference System (ANFIS). The book keeps you engaged with a systematic and detailed explanation of step-wise MATLAB-based implementation of electronic components. What you will learn Optimize various acceleration factors for exploring the residual life of components experimentally. Design an intelligent model to predict the upcoming faults and failures of electronic components and make provision for timely replacement of the fault components. Design experiments using Taguchis approach. Understand reliability modeling of active and passive components using the Artificial Neural Network and Fuzzy Logic. Who this book is for This book is for current and aspiring emerging tech professionals, researchers, students, and anyone who wishes to understand and diagnose the product life of electronic components using the power of artificial intelligence and various experimental techniques. Table of Contents 1. RELIABILITY FUNDAMENTALS 2. RELIABILITY MEASURES 3. REMAINING USEFUL LIFETIME ESTIMATION TECHNIQUES 4. INTELLIGENT MODELS FOR RELIABILITY PREDICTION 5. ACCELERATED LIFE TESTING 6. EXPERIMENTAL TESTING OF ACTIVE AND PASSIVE COMPONENTS 7. INTELLIGENT MODELING FOR RELIABILITY ASSESSMENT USING MATLAB About the Authors Dr Cherry Bhargava is working as an Associate Professor at the Department of Computer Science and Engineering, Symbiosis Institute of Technology, Pune, Maharashtra, India. She holds a Ph. D. (ECE) specialization in Artificial Intelligence, M. Tech (VLSI Design & CAD), and B. Tech (EIE) degrees. 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 18 books to her credit. She has registered six copyrights and filed twenty-one patents. Her four Australian innovation patents are granted. LinkedIn Profile: https://www. linkedin. com/in/dr-cherry-bhargava-7315619/ Dr. Pardeep Kumar Sharma is working as an associate professor at Lovely Professional University, Punjab, India. He has more than 14 years of teaching experience in the field of applied chemistry, artificial intelligence, DOE, and nanotechnology. He has completed his Ph. D. from Lovely Professional University and his post-graduation (Applied Chemistry) from Guru Nanak Dev University, Amritsar. LinkedIn Profile: https://www. linkedin. com/in/dr-pardeep-kumar-sharma-28581818/
