8,49 €
8,49 €
inkl. MwSt.
Sofort per Download lieferbar
0 °P sammeln
8,49 €
Als Download kaufen
8,49 €
inkl. MwSt.
Sofort per Download lieferbar
0 °P sammeln
Jetzt verschenken
Alle Infos zum eBook verschenken
8,49 €
inkl. MwSt.
Sofort per Download lieferbar
Alle Infos zum eBook verschenken
0 °P sammeln
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 Taguchi's approach, based on various acceleration factors.
An experimental approach using accelerated life testing is reconnoitered using examples of electrolytic capacitors. It explains how an Arrhenius equation based on MTBF, FIT, and RUL is predicted, thereby helping the user to estimate the end of the lifetime of components. It teaches how to use MATLAB tools for designing intelligent systems to run estimation of various reliability estimating parameters on electronic components.
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).
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 Taguchi's 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.
AUTHOR BIO
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.
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.
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 Taguchi's approach, based on various acceleration factors.
An experimental approach using accelerated life testing is reconnoitered using examples of electrolytic capacitors. It explains how an Arrhenius equation based on MTBF, FIT, and RUL is predicted, thereby helping the user to estimate the end of the lifetime of components. It teaches how to use MATLAB tools for designing intelligent systems to run estimation of various reliability estimating parameters on electronic components.
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).
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 Taguchi's 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.
AUTHOR BIO
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.
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.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, CY, CZ, D, DK, EW, E, FIN, F, GR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.