Advances in Computational Mathematics for Industrial System Reliability and Maintainability

2024
ISBN: 978-3-031-53513-0
Verlag: Springer Nature Switzerland

Buch, Englisch, 190 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 477 g

Reihe: Springer Series in Reliability Engineering

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.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Yazdi, Mohammad

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Produktionsmanagement, Qualitätskontrolle
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Produktionstechnik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

Introduction to Computational Mathematics in Industrial Systems.- Mathematical Models for Industrial System Reliability.- Maintenance Strategies and Optimization Techniques.- Computational Tools and Techniques for Reliability and Maintainability.- Reliability-Centered Design and System Resilience.- Integration of Computational Mathematics in Industrial Decision-Making.- Integration of IoT and Edge Computing in Industrial Systems.- Application of Quantum Computing in Reliability Analysis.- Digital Twins and Virtual Prototyping for Industrial Systems.- Augmented Reality (AR) and Virtual Reality (VR) in Maintenance Training.- Synthesizing Computational Mastery and Industrial Evolution - A Comprehensive. 

Über Autor(innen)

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.