Intelligent Reliability Analysis Using MATLAB and AI Perform Failure Analysis and Reliability Engineering using MATLAB and… (Bhargava, Dr. Cherry, Sharma, Dr. Pardeep Kumar) (Z-Library)
Author: Bhargava, Dr. Cherry, Sharma, Dr. Pardeep Kumar
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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. 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 an
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Intelligent Reliability Analysis Using MATLAB and AI Perform Failure Analysis and Reliability Engineering using MATLAB and Artificial Intelligence Dr. Cherry Bhargava Dr. Pardeep Kumar Sharma www.bpbonline.com
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FIRST EDITION 2021 Copyright © BPB Publications, India ISBN: 978-93-90684-656 All Rights Reserved. No part of this publication may be reproduced, distributed or transmitted in any form or by any means or stored in a database or retrieval system, without the prior written permission of the publisher with the exception to the program listings which may be entered, stored and executed in a computer system, but they can not be reproduced by the means of publication, photocopy, recording, or by any electronic and mechanical means. LIMITS OF LIABILITY AND DISCLAIMER OF WARRANTY The information contained in this book is true to correct and the best of author’s and publisher’s knowledge. The author has made every effort to ensure the accuracy of these publications, but publisher cannot be held responsible for any loss or damage arising from any information in this book. All trademarks referred to in the book are acknowledged as properties of their respective owners but BPB Publications cannot guarantee the accuracy of this information. Distributors:
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BPB PUBLICATIONS 20, Ansari Road, Darya Ganj New Delhi-110002 Ph: 23254990/23254991 MICRO MEDIA Shop No. 5, Mahendra Chambers, 150 DN Rd. Next to Capital Cinema, V.T. (C.S.T.) Station, MUMBAI-400 001 Ph: 22078296/22078297 DECCAN AGENCIES 4-3-329, Bank Street, Hyderabad-500195 Ph: 24756967/24756400
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BPB BOOK CENTRE 376 Old Lajpat Rai Market, Delhi-110006 Ph: 23861747 Published by Manish Jain for BPB Publications, 20 Ansari Road, Darya Ganj, New Delhi-110002 and Printed by him at Repro India Ltd, Mumbai www.bpbonline.com
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Dedicated to Our Parents & Our Loving Daughters, Mishty & Mauli
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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 has more than 16 years of teaching and research experience. She has a PhD (ECE) from the IKG Punjab Technical University, State Govt. University, Punjab, an M. Tech (VLSI Design & CAD) from Thapar University, and a B. Tech (EIE) from Kurukshetra University. She is a GATE-qualified with an All-India Rank of 428. She has authored about fifty technical research papers in SCI, Scopus indexed quality journals, and national/international conferences. She has eighteen books to her credit. She has registered six copyrights and filed twenty-one patents. Her four Australian innovation patents are granted. She is a recipient of various national and international awards for being an outstanding faculty in engineering and an excellent researcher. She is an active reviewer and editorial member of numerous prominent SCI and Scopus indexed journals. Her research area is Nanotechnology, Artificial Intelligence, and Data Science. Dr. Pardeep Kumar Sharma is working as an Associate Professor at the 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 a PhD from the Lovely Professional University, and a post- graduation degree (Applied Chemistry) from the Guru Nanak Dev University, Amritsar. He has authored more than twenty research
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papers in SCI, Scopus indexed quality journals, and national/international conferences. He has seven books to his credit, in the field of Nanotechnology and Artificial Intelligence. He has filed eighteen patents and registered two copyrights. His four Australian innovation patents are granted. He is a recipient of various national and international awards. He is an active reviewer and editorial board member of various indexed journals.
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About the Reviewers Deepak Kutty is a Reliability professional with nearly 15 years of experience in quality and reliability engineering across several industries. He has worked in different aspects of reliability, such as testing and analysis, field failure analysis, reliability growth, and DFR and analytics. He has a Master’s degree in quality and reliability from the Indian Statistical Institute, Kolkata, and a Bachelor’s degree in Mechanical Engineering from the Mumbai University. He currently works as a senior staff engineer in bloom energy in their Data Analytics department. N. Chaitanya Kumar Reddy, currently employed as a Reliability and Safety Engineer in AMETEK Instruments India Limited, has 10+ years of work experience in the area of Reliability and Safety for the Industrial Products related to Aerospace, Electronics etc. He completed his Master of Technology in Reliability Engineering in 2012 as a Gold Medalist of the batch, and the Bachelor of Technology in Electrical and Electronics Engineering in 2010 from JNT University. His interests include Scientific Research, and he has published papers in a number of reputed journals.
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Acknowledgement At this moment of my substantial enhancement, before we get into the thick of the things, we would like to add a few heartfelt words for the people who gave their unending support with their fair humor and warm wishes. First and foremost, praises and thanks to the God, the Almighty, for his showers of blessings throughout, to complete this book successfully. We want to acknowledge our students who provided us with the impetus to write a more suitable text. We are thankful to the management, seniors, and colleagues of Symbiosis International University and Lovely Professional University for constantly pushing us to move higher and higher. We would also like to thank all our friends, well-wishers, respondents, and academicians who us helped throughout our journey from inception to completion.
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Preface Due to the rapid evolution of the electronics device technology towards low cost and high performance, the electronic products become more complex, higher in density and speed, and lighter for easy portability. Reliability has become the major issue for the successful operation of an electronic device. During the life cycle of a component, reliability needs to be accessed at its different stages of life, i.e., at the design stage, manufacturing stage, launching stage, and operational stage. So, the assessing of the component performance at the different phases are necessary. After analyzing all the factors and parameters, the warranty period is extracted, which is mentioned along with the data sheet. The failure analysis explores the root cause of failure and then suggests the preventive and corrective measures, so that the overall performance of the system will not degrade. This book focuses on the failure analysis and fault prediction techniques using Artificial Intelligence. The failure prediction warns the user to replace the faulty component or the device before it deteriorates the entire system. It explores the residual life of the respective component or device in terms of the mean time between failure or the end of lifetime. To predict failure of any component or device, enormous methods and models have been used, i.e., the empirical method, analytical method, theoretical methods, experimental method, and artificial intelligence techniques etc. The necessary corrective actions for the failure of the electronic components are discussed in this book, using various examples.
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Over the 7 chapters in this book, you will learn the following: Chapter 1: [RELIABILITY FUNDAMENTALS] This chapter emphasises upon the fundamentals of reliability and life analysis. The concept of faults, failures, and errors are described using examples. The reliable data acquisition in the wireless sensor networks are discussed. Chapter 2: [RELIABILITY MEASURES] This chapter explains the importance of Reliability, Availability, Validity, and Maintainability. The need for the reliability analysis and prediction is discussed by considering examples of the various electronic components. Chapter 3: [REMAINING USEFUL LIFETIME ESTIMATION TECHNIQUES] This chapter discusses the significance of the Remaining Useful Lifetime and the concept of e-waste minimization. The various empirical, experimental, and mathematical models for the RUL prediction are discussed along with the applications. Chapter 4: [INTELLIGENT MODELS FOR RELIABILITY PREDICTION]
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This chapter explains about the application of the artificial intelligence techniques for the reliability prediction and the RUL estimation. An intelligent model is deployed, which warns the user for the upcoming fault or failure, so that the user can replace the faulty product well before its expiry/actual failure. Chapter 5: [ACCELERATED LIFE TESTING] This chapter discusses the experimental approach for analyzing the reliability and residual lifetime of the electronic components. An Arrhenius equation based accelerated life testing method is used as an experimental technique. The design of experiments is conducted using the Taguchi’s method for the electrolytic capacitor. Chapter 6: [EXPERIMENTAL TESTING OF ACTIVE AND PASSIVE COMPONENTS] This chapter explains the experimental test approach for the reliability analysis using examples of the various active and passive electronic components. The calculation of the different reliability parameters such as FIT, MTBF, and reliability are elaborated in this chapter. Chapter 7: [INTELLIGENT MODELLING FOR RELIABILITY ASSESMENT USING MATLAB] This chapter explains the MATLAB based intelligent modelling for the reliability assessment of the various active and passive components, such as the capacitor, resistor, or inductor. The
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Artificial Neural Network (ANN), Fuzzy Logic (FL), and Adaptive Neuro-Fuzzy Inference System (ANFIS) are explored for the reliability prediction of the electronic components.
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Downloading the coloured images: Please follow the link to download the Coloured Images of the book: https://rebrand.ly/1gl3zq9 Errata We take immense pride in our work at BPB Publications and follow best practices to ensure the accuracy of our content to provide with an indulging reading experience to our subscribers. Our readers are our mirrors, and we use their inputs to reflect and improve upon human errors, if any, that may have occurred during the publishing processes involved. To let us maintain the quality and help us reach out to any readers who might be having difficulties due to any unforeseen errors, please write to us at : errata@bpbonline.com Your support, suggestions and feedbacks are highly appreciated by the BPB Publications’ Family.
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Table of Contents 1. Reliability Fundamentals Introduction Structure Objectives Reliability Failure Role of probability laws in reliability theory Hazard rate Weibull distribution Some important measures related to reliability analysis Probability of survival Mean Time Between Failures [E(T)] Failure rate or Hazard rate Hazard function [h(t)] Failure density function [f(t)] Configuration in the context of reliability analysis Series configuration Parallel configuration Mixed configuration Series-parallel configuration Parallel-series configuration Reliability analysis of Wireless Sensor Networks Wireless Sensor Networks and data acquisition systems Constraints of Wireless Sensor Networks Methods for Wireless Sensor Networks Evolution of Wireless Sensor and Actuator networks Centralized decision-making architecture Distributed decision-making architecture
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Modes of Data Acquisition Reliable Data Acquisition Issues in reliable data acquisition Application areas of reliability Conclusion Questions 2. Reliability Measures Introduction Structure Objectives Introduction Definition and scope of reliability Probability Adequate performance Specified time Operating conditions Reliability measures Reliability Maintainability Availability Point availability Mean availability Steady state availability Inherent availability Achieved availability Operational availability Mean Time to Failure (MTTF) Mean Time to Repair (MTTR) Mean Time Between Failure (MTBF)
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