Overview
- Covers reliability and maintainability tools and their applications to industrial systems
- Explores mathematical models for reliability, covering probability theory, and statistical methods
- Includes real-world case studies and applications that illustrate practical implementation
Part of the book series: Springer Series in Reliability Engineering (RELIABILITY)
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About this book
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.
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Keywords
- Computational Mathematics
- Industrial Systems
- Reliability
- Maintainability
- Mathematical Models
- Optimization Techniques
- Simulation Methods
- Data Analysis
- Artificial Intelligence
- Machine Learning
- Maintenance Strategies
- Resilience Analysis
- Decision-Making
- Cost-Benefit Analysis
- Asset Management
- Robust Design
- Risk Assessment
- Case Studies
- Implementation Challenges
- Future Trends
Table of contents (11 chapters)
Authors and Affiliations
About the author
Mohammad Yazdi's illustrious academic and professional journey began with his BSc in Safety and Technical Protection Engineering from the Petroleum University of Technology in Abadan, Iran, conferred in 2012. He further elevated his educational prowess by obtaining an MSc degree in Industrial Engineering from the Eastern Mediterranean University in Famagusta, Cyprus, in 2017. Immediately after, Mohammad integrated his expertise into academia by affiliating with the Centre for Marine Technology and Ocean Engineering (CENTEC) at the University of Lisbon in Portugal. He made significant contributions both in-person during 2017 and 2018 and remotely in 2019. His relentless pursuit of knowledge led him to undertake a dual Ph.D. program in 2022, partnering with the Centre for Risk, Integrity, and Safety Engineering (C-RISE) at the Memorial University of Newfoundland, Canada, and Macquarie University in Australia. Before venturing into these academic achievements, Mohammad dedicated himself to practical applications in the industrial world from 2012 to 2016. He took on multifaceted roles such as a Firefighter, Safety Officer, WHS/OHS Advisor, and Auditor, serving vital sectors including power plants, and the oil and gas industry. His research interests and professional background converge at the nexus of system safety, risk assessment, resilience, process integrity, and asset management, especially concerning renewable and non-renewable energy infrastructure. With an impressive track record of leading large-scale energy projects and technology-rich initiatives, Mohammad offers invaluable support to asset operators, developers, and maintainers.
Passionately, he endeavors to bridge the gap between industry and academia, crafting innovative solutions that foster advanced decision-making, systems thinking, and creativity. Mohammad champions an asset lifecycle approach from capital investment planning, spanning through operation, maintenance, and culminating in disposal. This holistic perspective allows him to integrate pragmatic thinking, balancing superior business outcomes with optimum functionality and reliability.
Accessibility Information
Bibliographic Information
Book Title: Advances in Computational Mathematics for Industrial System Reliability and Maintainability
Authors: Mohammad Yazdi
Series Title: Springer Series in Reliability Engineering
DOI: https://doi.org/10.1007/978-3-031-53514-7
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
Hardcover ISBN: 978-3-031-53513-0Published: 25 February 2024
Softcover ISBN: 978-3-031-53516-1Published: 14 March 2025
eBook ISBN: 978-3-031-53514-7Published: 24 February 2024
Series ISSN: 1614-7839
Series E-ISSN: 2196-999X
Edition Number: 1
Number of Pages: XIV, 190
Number of Illustrations: 1 b/w illustrations
Topics: Production, Industrial and Production Engineering, Artificial Intelligence, Mathematical Modeling and Industrial Mathematics, Engineering Mathematics