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Engineering Reliability and Risk Assessment. Advances in Reliability Science

  • Book

  • September 2022
  • Elsevier Science and Technology
  • ID: 5562065

Engineering Reliability and Risk Assessment explains how to improve the performance of a system using the latest risk and reliability models. Against a backdrop of increasing availability of industrial data, and ever-increasing global commercial competition, the standards for optimal efficiency with minimum hazards keep improving. Topics explained include Effective strategies for the maintenance of the mechanical components of a system, How to schedule necessary interventions throughout the product life cycle, How to understand the structure and cost of complex systems, Planning a schedule to improve the reliability and life of the system, software, system safety and risk informed asset management, and more.

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Table of Contents

1. Bayesian networks for failure analysis of complex systems using different data sources 2. Hybrid failure modes and effect analysis model for reliability and safety evaluation of pressurized steam trap 3. Reliability and availability analysis of a standby system with activation time and varying demand 4. Fuzzy attack tree analysis of security threat assessment in an internet security system using algebraic t-norm and t-conorm 5. A new flexible extension to a lifetime distributions, properties, inference, and applications in engineering science 6. Markov and semi-Markov models in system reliability 7. Emerging trends and future directions in software reliability growth modelling 8. Reliability and profit analysis of a markov model having cost-free warranty with waiting repair facility 9. Semi-Markov modeling applications in system availability analysis 10. An a-cut interval-based similarity aggregation method to evaluate fault tree events for system safety under fuzzy environment 11. Business analytics to advance industrial safety management 12. Risk assessment and management of fire-induced domino effects in chemical industrial park 13. Stability assessment using Bayesian network control for inverters in smart grid

Authors

Harish Garg Associate Professor, School of Mathematics, Thapar Institute of Engineering and Technology, Patiala, Punjab, India. Dr. Garg is one of the pioneer researchers in the world. He ranks in the World's Top 2% Scientist List and Rank #1 in India & World Rank #229 published by Stanford University in the consecutive three years 2020, 2021, and 2022. He is the recipient of the Obada-Prize 2022 - Young Distinguished Researchers. He is also the recipient of the Top-Cited paper by an India-based author (2015 - 2019) from Elsevier Publisher. He also serves as an advisory board member of the Universal Scientific Education and Research Network (USERN).
Dr. Garg's research interests include Computational Intelligence, Multi-criteria decision making, Evolutionary algorithms, Reliability analysis, Expert systems, and decision support systems, Computing with words, and Soft Computing. He has authored more than 400 papers (over 350 are SCI) published in refereed International Journals including IEEE Transactions, Elsevier, Springer, etc. He has also authored seven book chapters. Also, he edited 8 books from Elsevier, Springer, and other publishers. His Google citations are over 17650 with an H-index of- 75. Dr. Garg also serves on editorial boards of several leading international journals, this includes the Founding Editor-in-Chief of the Journal of Computational and Cognitive Engineering. He is also the Associate Editor of IEEE Transaction of Fuzzy Systems, Soft Computing, Alexandria Engineering Journal, Journal of Intelligent & Fuzzy Systems, Complex and Intelligent Systems, Journal of Industrial & Management Optimization, CAAI Transactions on Intelligence Technology, etc.

Dr. Garg also shared his knowledge (Teaching as well as Research) with the whole world through their YouTube channel https://www.youtube.com/c/DrHarishGarg. For more details about him, kindly follow his webpage https://sites.google.com/site/harishg58iitr/home Mangey Ram Department of Mathematics; Computer Science and Engineering, Research Professor, Graphic Era (Deemed to be University), Dehradun, India. Prof. Mangey Ram received the Ph.D. degree major in Mathematics and minor in Computer Science from G. B. Pant University of Agriculture and Technology, Pantnagar, India. He has been a Faculty Member for around fourteen years and has taught several core courses in pure and applied mathematics at undergraduate, postgraduate, and doctorate levels. He is currently the Research Professor at Graphic Era (Deemed to be University), Dehradun, India & Visiting Professor at Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, Russia. Before joining the Graphic Era, he was a Deputy Manager (Probationary Officer) with Syndicate Bank for a short period.