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Reliability Engineering and Computational Intelligence for Complex Systems

Design, Analysis and Evaluation

  • Book
  • © 2023

Overview

  • Addresses current issues in reliability analysis of complex systems
  • Deals with application of artificial intelligence and machine learning in reliability engineering
  • Treats effective, real-life applications for the merger of reliability engineering and computational intelligence

Part of the book series: Studies in Systems, Decision and Control (SSDC, volume 496)

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Table of contents (13 chapters)

  1. Mathematical Methods for Reliability Engineering and Computational Intelligence

  2. Digital Techniques for Reliability Engineering and Computational Intelligence

  3. Use Cases for Reliability Engineering and Computational Intelligence

Keywords

About this book

This book offers insight into the current issues of the merger between reliability engineering and computational intelligence. The intense development of information technology allows for designing more complex systems as well as creating more detailed models of real-world systems which forces traditional reliability engineering approaches based on Boolean algebra, probability theory, and statistics to embrace the world of data science. The works deal with methodological developments as well as applications in the development of safe and reliable systems in various kinds of distribution networks, in the development of highly reliable healthcare systems, in finding weaknesses in systems with the human factor, or in reliability analysis of large information systems and other software solutions.

In this book, experts from various fields of reliability engineering and computational intelligence present their view on the risks, the opportunities and the synergy between reliability engineering and computational intelligence that have been developed separately but in recent years have found a way to each other. The topics addressed include the latest advances in computing technology to improve the real lives of millions of people by increasing safety and reliability of various types of real-life systems by increasing the availability of software services, reducing the accident rate of means of transport, developing high reliable patient-specific health care, or generally, save cost and increase efficiency in the work and living environment. Though this book, the reader has access to professionals and researchers in the fields of reliability engineering and computational intelligence that share their experience in merging the two as well as an insight into the latest methods, concerns and application domains. 

Editors and Affiliations

  • Computing and Engineering, United Kingdom and TNO, Healthy Living & Work, Leiden, University of Huddersfield, Huddersfield, The Netherlands

    Coen van Gulijk

  • Faculty of Management Science and Informatics, University of Zilina, Zilina, Slovakia

    Elena Zaitseva, Miroslav Kvassay

About the editors

Coen van Gulijk re-joined TNO in the Netherlands after a five-year post as full professor at the University of Huddersfield at the school of computing and engineering. He remains academically active as a visiting professor at the school of computing and engineering at the University of Huddersfield. His work focuses on the IT transformation Risk Analysis and Safety Management Systems. The objective is to provide industries with modern IT business systems to support risk-based decision making and asset management and to deliver cost reductions, performance enhancements, and optimization in industry. The introduction of AI functionality in safety management software is of special interest. Coen received a Ph.D. degree chemical engineering, applying computational fluid dynamics for aerosol deposition in diesel exhaust gasses. He has produced over 100 scientific papers on various topics and edited and co-edited half a dozen of multi-author books and proceedings.

Elena Zaitseva received the M.S. degree in computer science from the Belarus State University of Informatics and Radioelectronics (BSUIR), Belarus, in 1989 and the Ph.D. degree in computer science from BSUIR in 1994. She worked as Associate Professor at the Department of Informatics of University of Zilina, Slovakia, from 2004 to 2015. Since 2015, she has been Professor at the same department. Her research interests include Reliability Analysis of Multi-state System, Fuzzy Decision Trees, and Decision Support Systems. She is Chair of the Technical Committee of European Safety and Reliability Association. She has more than 140 documents indexed in Scopus and more than 500 citations.

Miroslav Kvassay received the M.S. degree in information systems and the Ph.D. degree in applied informatics from the University of Zilina, Slovakia, in 2012 and 2015, respectively. From 2015 to 2019, he was Assistant Professor at the Department of Informatics of University of Zilina, Slovakia. Since 2019, he has been Associate Professor at the same department. His research interests include applications of Boolean and Multiple-Valued Logic in Reliability Analysis of Binary- and Multi-state Systems, respectively. He has more than 80 documents indexed in Scopus and more than 200 citations.

Bibliographic Information

  • Book Title: Reliability Engineering and Computational Intelligence for Complex Systems

  • Book Subtitle: Design, Analysis and Evaluation

  • Editors: Coen van Gulijk, Elena Zaitseva, Miroslav Kvassay

  • Series Title: Studies in Systems, Decision and Control

  • DOI: https://doi.org/10.1007/978-3-031-40997-4

  • Publisher: Springer Cham

  • eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023

  • Hardcover ISBN: 978-3-031-40996-7Published: 24 September 2023

  • Softcover ISBN: 978-3-031-40999-8Due: 25 October 2023

  • eBook ISBN: 978-3-031-40997-4Published: 23 September 2023

  • Series ISSN: 2198-4182

  • Series E-ISSN: 2198-4190

  • Edition Number: 1

  • Number of Pages: VIII, 225

  • Number of Illustrations: 16 b/w illustrations, 93 illustrations in colour

  • Topics: Computational Intelligence, Machine Learning, Engineering Design

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