Predictive Analytics in System Reliability
Predictive Analytics in System Reliability

Author: Vijay Kumar

Publisher: Springer Nature

Published: 2022-09-08

Total Pages: 286

ISBN-13: 3031053478

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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
Predictive Analytics

Author: Vijay Kumar

Publisher: CRC Press

Published: 2021-01-13

Total Pages: 289

ISBN-13: 1000332861

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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 Data Collection and Analysis
Reliability Data Collection and Analysis

Author: J. Flamm

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 323

ISBN-13: 9401124388

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The ever increasing public demand and the setting-up of national and international legislation on safety assessment of potentially dangerous plants require that a correspondingly increased effort be devoted by regulatory bodies and industrial organisations to collect reliability data in order to produce safety analyses. Reliability data are also needed to assess availability of plants and services and to improve quality of production processes, in particular, to meet the needs of plant operators and/or designers regarding maintenance planning, production availability, etc. The need for an educational effort in the field of data acquisition and processing has been stressed within the framework of EuReDatA, an association of organisations operating reliability data banks. This association aims to promote data exchange and pooling of data between organisations and to encourage the adoption of compatible standards and basic definitions for a consistent exchange of reliability data. Such basic definitions are considered to be essential in order to improve data quality. To cover issues directly linked to the above areas ample space is devoted to the definition of failure events, common cause and human error data, feedback of operational and disturbance data, event data analysis, lifetime distributions, cumulative distribution functions, density functions, Bayesian inference methods, multivariate analysis, fuzzy sets and possibility theory, etc.

Reliability and Availability Engineering
Reliability and Availability Engineering

Author: Kishor S. Trivedi

Publisher: Cambridge University Press

Published: 2017-08-03

Total Pages: 729

ISBN-13: 1107099501

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Learn about the techniques used for evaluating the reliability and availability of engineered systems with this comprehensive guide.

Reliability Modeling, Analysis And Optimization
Reliability Modeling, Analysis And Optimization

Author: Hoang Pham

Publisher: World Scientific

Published: 2006-06-26

Total Pages: 506

ISBN-13: 9814479993

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As our modern information-age society grows in complexity both in terms of embedded systems and applications, the problems and challenges in reliability become ever more complex. Bringing together many of the leading experts in the field, this volume presents a broad picture of current research on system modeling and optimization in reliability and its applications.The book comprises twenty-three chapters organized into four parts: Reliability Modeling, Software Quality Engineering, Software Reliability, and Maintenance and Inspection Policies. These sections cover a wide range of important topics, including system reliability modeling, optimization, software reliability and quality, maintenance theory and inspection, reliability failure analysis, sampling plans and schemes, software development processes and improvement, stochastic process modeling, statistical distributions and analysis, fault-tolerant performance, software measurements and cost effectiveness, queueing theory and applications, system availability, reliability of repairable systems, testing sampling inspection, software capability maturity model, accelerated life modeling, statistical control, and HALT testing.

Advanced Data Analytics for Power Systems
Advanced Data Analytics for Power Systems

Author: Ali Tajer

Publisher: Cambridge University Press

Published: 2021-04-08

Total Pages: 601

ISBN-13: 1108494757

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Experts in data analytics and power engineering present techniques addressing the needs of modern power systems, covering theory and applications related to power system reliability, efficiency, and security. With topics spanning large-scale and distributed optimization, statistical learning, big data analytics, graph theory, and game theory, this is an essential resource for graduate students and researchers in academia and industry with backgrounds in power systems engineering, applied mathematics, and computer science.

System Reliability and Security
System Reliability and Security

Author: Javaid Iqbal

Publisher: CRC Press

Published: 2023-12-07

Total Pages: 273

ISBN-13: 1003808107

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Because of the growing reliance on software, concerns are growing as to how reliable a system is before it is commissioned for use, how high the level of reliability is in the system, and how many vulnerabilities exist in the system before its operationalization. Equally pressing issues include how to secure the system from internal and external security threats that may exist in the face of resident vulnerabilities. These two problems are considered increasingly important because they necessitate the development of tools and techniques capable of analyzing dependability and security aspects of a system. These concerns become more pronounced in the cases of safety-critical and mission-critical systems. System Reliability and Security: Techniques and Methodologies focuses on the use of soft computing techniques and analytical techniques in the modeling and analysis of dependable and secure systems. It examines systems and applications having complex distributed or networked architectures in such fields as: Nuclear energy Ground transportation systems Air traffic control Healthcare and medicine Communications System reliability engineering is a multidisciplinary field that uses computational methods for estimating or predicting the reliability aspects of a system and analyzing failure data obtained from real-world projects. System security is a related field that ensures that even a reliable system is secure against accidental or deliberate intrusions and is free of vulnerabilities. This book covers tools and techniques, cutting-edge research topics, and methodologies in the areas of system reliability and security. It examines prediction models and methods as well as how to secure a system as it is being developed.

Reliability Growth
Reliability Growth

Author: Panel on Reliability Growth Methods for Defense Systems

Publisher: National Academy Press

Published: 2015-03-01

Total Pages: 235

ISBN-13: 9780309314749

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A high percentage of defense systems fail to meet their reliability requirements. This is a serious problem for the U.S. Department of Defense (DOD), as well as the nation. Those systems are not only less likely to successfully carry out their intended missions, but they also could endanger the lives of the operators. Furthermore, reliability failures discovered after deployment can result in costly and strategic delays and the need for expensive redesign, which often limits the tactical situations in which the system can be used. Finally, systems that fail to meet their reliability requirements are much more likely to need additional scheduled and unscheduled maintenance and to need more spare parts and possibly replacement systems, all of which can substantially increase the life-cycle costs of a system. Beginning in 2008, DOD undertook a concerted effort to raise the priority of reliability through greater use of design for reliability techniques, reliability growth testing, and formal reliability growth modeling, by both the contractors and DOD units. To this end, handbooks, guidances, and formal memoranda were revised or newly issued to reduce the frequency of reliability deficiencies for defense systems in operational testing and the effects of those deficiencies. "Reliability Growth" evaluates these recent changes and, more generally, assesses how current DOD principles and practices could be modified to increase the likelihood that defense systems will satisfy their reliability requirements. This report examines changes to the reliability requirements for proposed systems; defines modern design and testing for reliability; discusses the contractor's role in reliability testing; and summarizes the current state of formal reliability growth modeling. The recommendations of "Reliability Growth" will improve the reliability of defense systems and protect the health of the valuable personnel who operate them.

Intelligent Computing on IoT 2.0, Big Data Analytics, and Block Chain Technology
Intelligent Computing on IoT 2.0, Big Data Analytics, and Block Chain Technology

Author: Mohammad S. Obaidat

Publisher: CRC Press

Published: 2024-05-23

Total Pages: 418

ISBN-13: 1040019633

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The book is designed as a reference text and explores the concepts and techniques of IoT, artificial intelligence (AI), and blockchain. It also discusses the possibility of applying blockchain for providing security in various domains. The specific highlight of this book is focused on the application of integrated technologies in enhancing data models, better insights and discovery, intelligent predictions, smarter finance, smart retail, global verification, transparent governance, and innovative audit systems. The book discusses the potential of blockchain to significantly increase data while boosting accuracy and integrity in IoT-generated data and AI-processed information. It elucidates definitions, concepts, theories, and assumptions involved in smart contracts and distributed ledgers related to IoT systems and AI approaches. The book offers real-world uses of blockchain technologies in different IoT systems and further studies its influence in supply chains and logistics, the automotive industry, smart homes, the pharmaceutical industry, agriculture, and other areas. It also presents readers with ways of employing blockchain in IoT and AI, helping them to understand what they can and cannot do with blockchain. The book is aimed primarily at advanced undergraduates and graduates studying computer science, computer engineering, electrical engineering, information systems, computational sciences, artificial intelligence, and information technology. Researchers and professionals will also find this book very useful.

Intelligent Data Analytics for Power and Energy Systems
Intelligent Data Analytics for Power and Energy Systems

Author: Hasmat Malik

Publisher: Springer Nature

Published: 2022-02-17

Total Pages: 649

ISBN-13: 9811660816

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This book brings together state-of-the-art advances in intelligent data analytics as driver of the future evolution of PaE systems. In the modern power and energy (PaE) domain, the increasing penetration of renewable energy sources (RES) and the consequent empowerment of consumers as a central and active solution to deal with the generation and development variability are driving the PaE system towards a historic paradigm shift. The small-scale, diversity, and especially the number of new players involved in the PaE system potentiate a significant growth of generated data. Moreover, advances in communication (between IoT devices and M2M: machine to machine, man to machine, etc.) and digitalization hugely increased the volume of data that results from PaE components, installations, and systems operation. This data is becoming more and more important for PaE systems operation, maintenance, planning, and scheduling with relevant impact on all involved entities, from producers, consumer,s and aggregators to market and system operators. However, although the PaE community is fully aware of the intrinsic value of those data, the methods to deal with it still necessitate substantial enhancements, development and research. Intelligent data analytics is thereby playing a fundamental role in this domain, by enabling stakeholders to expand their decision-making method and achieve the awareness on the PaE environment. The editors also included demonstrated codes for presented problems for better understanding for beginners.