Predictive Analytics In System Reliability

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Predictive Analytics In System Reliability

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Author : Vijay Kumar
language : en
Publisher: Springer Nature
Release Date : 2022-09-08

Predictive Analytics In System Reliability written by Vijay Kumar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-08 with Mathematics categories.

This book provides engineers and researchers knowledge to help them in system reliability analysis using machine learning, artificial intelligence, big data, genetic algorithm, information theory, multi-criteria decision making, and other techniques. It will also be useful to students learning reliability engineering. The book brings readers up to date with how system reliability relates to the latest techniques of AI, big data, genetic algorithm, information theory, and multi-criteria decision making and points toward future developments in the subject.

Predictive Analytics

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Author : Vijay Kumar
language : en
Publisher: CRC Press
Release Date : 2021-01-13

Predictive Analytics written by Vijay Kumar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-13 with Mathematics categories.

Predictive analytics refers to making predictions about the future based on different parameters which are historical data, machine learning, and artificial intelligence. This book provides the most recent advances in the field along with case studies and real-world examples. It discusses predictive modeling and analytics in reliability engineering and introduces current achievements and applications of artificial intelligence, data mining, and other techniques in supply chain management. It covers applications to reliability engineering practice, presents numerous examples to illustrate the theoretical results, and considers and analyses case studies and real-word examples. The book is written for researchers and practitioners in the field of system reliability, quality, supply chain management, and logistics management. Students taking courses in these areas will also find this book of interest.

Predictive Analytics

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Author : Vijay Kumar
language : en
Publisher: CRC Press
Release Date : 2021-01-14

Predictive Analytics written by Vijay Kumar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-14 with Technology & Engineering categories.

Predictive analytics refers to making predictions about the future based on different parameters which are historical data, machine learning, and artificial intelligence. This book provides the most recent advances in the field along with case studies and real-world examples. It discusses predictive modeling and analytics in reliability engineering and introduces current achievements and applications of artificial intelligence, data mining, and other techniques in supply chain management. It covers applications to reliability engineering practice, presents numerous examples to illustrate the theoretical results, and considers and analyses case studies and real-word examples. The book is written for researchers and practitioners in the field of system reliability, quality, supply chain management, and logistics management. Students taking courses in these areas will also find this book of interest.

Reliability Engineering And Failure Analysis For Electromechanical Systems

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Author : AKSHAY GAIKWAD DR. SHAKEB KHAN
language : en
Publisher: DeepMisti Publication
Release Date : 2024-12-22

Reliability Engineering And Failure Analysis For Electromechanical Systems written by AKSHAY GAIKWAD DR. SHAKEB KHAN and has been published by DeepMisti Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-22 with Computers categories.

In the evolving landscape of electromechanical systems, ensuring reliability and minimizing failure rates are critical to maintaining optimal performance and operational efficiency. This book, Reliability Engineering and Failure Analysis for Electromechanical Systems, is designed to address the complexities of system reliability, offering both theoretical insights and practical guidance for understanding and mitigating failure modes in electromechanical systems. Our goal is to provide readers with the knowledge and tools necessary to enhance the performance, safety, and durability of these systems across a range of industries. This book presents a comprehensive exploration of the methodologies, techniques, and best practices employed in the reliability engineering and failure analysis of electromechanical systems. From fundamental concepts to advanced techniques, we examine the critical strategies for ensuring the reliability of these systems, with a focus on the analysis and prevention of failures. The content is crafted to be accessible and valuable to a diverse audience, including students, engineers, system designers, and industry professionals involved in the development, maintenance, and optimization of electromechanical systems. In crafting this book, we have drawn upon the latest research, case studies, and industry standards to provide readers with both a solid theoretical foundation and actionable insights for addressing reliability challenges. The chapters are structured to offer a balance of depth and practical application, covering topics such as failure modes and effects analysis (FMEA), root cause analysis, reliability modeling, and predictive maintenance strategies. Additionally, we dedicate sections to the importance of failure prevention, focusing on the integration of reliability engineering into the design process, as well as approaches to risk management and performance enhancement. The inspiration for this book arises from the vital role that network health plays in the stability and scalability of cloud platforms. We are profoundly grateful to Chancellor Shri Shiv Kumar Gupta of Maharaja Agrasen Himalayan Garhwal University for his unwavering support and vision. His dedication to fostering academic excellence and promoting a culture of innovation has been instrumental in bringing this project to fruition. We hope this book serves as a comprehensive and practical resource for those seeking to deepen their understanding of reliability engineering and failure analysis in electromechanical systems. We believe that the insights shared in these pages will empower readers to innovate and implement solutions that enhance the resilience and longevity of electromechanical systems in today’s demanding environments. Thank you for joining us on this journey toward greater system reliability and performance. Authors

Practical Applications Of Bayesian Reliability

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Author : Yan Liu
language : en
Publisher: John Wiley & Sons
Release Date : 2019-05-28

Practical Applications Of Bayesian Reliability written by Yan Liu and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-28 with Technology & Engineering categories.

Demonstrates how to solve reliability problems using practical applications of Bayesian models This self-contained reference provides fundamental knowledge of Bayesian reliability and utilizes numerous examples to show how Bayesian models can solve real life reliability problems. It teaches engineers and scientists exactly what Bayesian analysis is, what its benefits are, and how they can apply the methods to solve their own problems. To help readers get started quickly, the book presents many Bayesian models that use JAGS and which require fewer than 10 lines of command. It also offers a number of short R scripts consisting of simple functions to help them become familiar with R coding. Practical Applications of Bayesian Reliability starts by introducing basic concepts of reliability engineering, including random variables, discrete and continuous probability distributions, hazard function, and censored data. Basic concepts of Bayesian statistics, models, reasons, and theory are presented in the following chapter. Coverage of Bayesian computation, Metropolis-Hastings algorithm, and Gibbs Sampling comes next. The book then goes on to teach the concepts of design capability and design for reliability; introduce Bayesian models for estimating system reliability; discuss Bayesian Hierarchical Models and their applications; present linear and logistic regression models in Bayesian Perspective; and more. Provides a step-by-step approach for developing advanced reliability models to solve complex problems, and does not require in-depth understanding of statistical methodology Educates managers on the potential of Bayesian reliability models and associated impact Introduces commonly used predictive reliability models and advanced Bayesian models based on real life applications Includes practical guidelines to construct Bayesian reliability models along with computer codes for all of the case studies JAGS and R codes are provided on an accompanying website to enable practitioners to easily copy them and tailor them to their own applications Practical Applications of Bayesian Reliability is a helpful book for industry practitioners such as reliability engineers, mechanical engineers, electrical engineers, product engineers, system engineers, and materials scientists whose work includes predicting design or product performance.

Big Data Analytics For Cyber Physical System In Smart City

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Author : Mohammed Atiquzzaman
language : en
Publisher: Springer Nature
Release Date : 2020-12-17

Big Data Analytics For Cyber Physical System In Smart City written by Mohammed Atiquzzaman and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-17 with Computers categories.

This book gathers a selection of peer-reviewed papers presented at the second Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2020) conference, held in Shanghai, China, on 28–29 December 2020. The contributions, prepared by an international team of scientists and engineers, cover the latest advances made in the field of machine learning, and big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.

Emerging Methods In Predictive Analytics Risk Management And Decision Making

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Author : Hsu, William H.
language : en
Publisher: IGI Global
Release Date : 2014-01-31

Emerging Methods In Predictive Analytics Risk Management And Decision Making written by Hsu, William H. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-31 with Business & Economics categories.

Decision making tools are essential for the successful outcome of any organization. Recent advances in predictive analytics have aided in identifying particular points of leverage where critical decisions can be made. Emerging Methods in Predictive Analytics: Risk Management and Decision Making provides an interdisciplinary approach to predictive analytics; bringing together the fields of business, statistics, and information technology for effective decision making. Managers, business professionals, and decision makers in diverse fields will find the applications and cases presented in this text essential in providing new avenues for risk assessment, management, and predicting the future outcomes of their decisions.

Data Analytics In System Engineering

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Author : Radek Silhavy
language : en
Publisher: Springer Nature
Release Date : 2024-02-23

Data Analytics In System Engineering written by Radek Silhavy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-23 with Computers categories.

These proceedings offer an insightful exploration of integrating data analytics in system engineering. This book highlights the essential role of data in driving innovation, optimizing processes, and solving complex challenges in the field. Targeted at industry professionals, researchers, and enthusiasts, this book serves as a comprehensive resource, providing actionable insights and showcasing transformative applications of data in engineering. It is a must-read for anyone keen on understanding and participating in the ongoing evolution of system engineering in our data-centric world.

Big Data Analytics For Cyber Physical Systems

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Author : Shiyan Hu
language : en
Publisher: Springer Nature
Release Date : 2020-06-25

Big Data Analytics For Cyber Physical Systems written by Shiyan Hu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-25 with Computers categories.

This book highlights research and survey articles dedicated to big data techniques for cyber-physical system (CPS), which addresses the close interactions and feedback controls between cyber components and physical components. The book first discusses some fundamental big data problems and solutions in large scale distributed CPSs. The book then addresses the design and control challenges in multiple CPS domains such as vehicular system, smart city, smart building, and digital microfluidic biochips. This book also presents the recent advances and trends in the maritime simulation system and the flood defence system.

Advances In Computational Mathematics For Industrial System Reliability And Maintainability

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Author : Mohammad Yazdi
language : en
Publisher: Springer Nature
Release Date : 2024-02-24

Advances In Computational Mathematics For Industrial System Reliability And Maintainability written by Mohammad Yazdi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-24 with Business & Economics categories.

This book is a comprehensive exploration of computational mathematics and its impact on enhancing the reliability and maintainability of industrial systems. With its careful blend of theoretical foundations, practical applications, and future perspectives, this book is a vital reference for researchers, engineers, and professionals seeking to optimize industrial systems' performance, efficiency, and resilience.