This book explores a wide range of topics in reliability and maintenance engineering, including fault diagnosis, prognostics, condition monitoring, risk assessment, optimization, and decision-making. By leveraging computational intelligence techniques—such as artificial intelligence, machine learning, evolutionary algorithms, fuzzy logic, and neural networks—it presents innovative solutions for improving the dependability and lifecycle performance of critical systems and assets.

Its primary aim is to bridge the gap between theory and real-world practice, offering insights that combine academic research with industrial applications. Researchers, practitioners, and students in reliability engineering, maintenance management, industrial engineering, and computational intelligence will find a valuable resource for strengthening their knowledge and skill set in data-driven reliability improvement.

Special features include practical case studies, hands-on examples, and implementation strategies that demonstrate how intelligent methods can be applied across real maintenance scenarios. The book adopts a multidisciplinary perspective, drawing on expertise from multiple domains to provide a holistic understanding of reliability challenges and smart solutions.

Mohamed Arezki Mellal is a Professor in the Department of Mechanical Engineering, Faculty of Technology, at M’Hamed Bougara University, Boumerdes, Algeria. He was ranked among the Top 2% of Scientists Worldwide by Stanford University (single-year 2022) and was the top-ranked candidate in the 47th National University Commission for the Professorship in Mechanical Engineering in 2022. He has been a Visiting Scholar at various universities and has published over 80 research works. He has been invited to numerous conferences and serves as a regular reviewer for over 30 SCIE journals. He was involved in the international project “Algerian National Laboratory for Maintenance Education” in conjunction with the European Union (Erasmus+). He has supervised numerous dissertations, has been an invited keynote speaker at various conferences, and served as a session chair for the 2nd and 3rd International Conference on System Reliability and Safety, ICSRS 2017 and 2018, held in Milan (Italy) and Barcelona (Spain), respectively. He also chaired sessions at the 8th International Conference on Mechatronics, Electronics and Automation Engineering (ICMEAE 2021), Beijing, China, and the 5th International Conference on Mathematical Techniques in Engineering Applications, Dehradun, India, 2021. Prof. Mellal was recognized as the Best Reviewer for the International Conference on Vision, Image and Signal Processing (ICVISP) in 2017 and 2018, held in Osaka (Japan) and Las Vegas (USA), respectively. He is an Associate Editor for the journal Frontiers in Mechanical Engineering (Topic: Mechatronics) – IF = 2.3. He has served as a committee member for over 80 international conferences and acted as a for journal special sessions. His research interests encompass mechatronics, nature-inspired techniques for solving engineering optimization problems, including system design and dependability, energy management, control, robotics, and manufacturing.

Harish Garg working as an Associate Professor at Thapar Institute of Engineering & Technology, Patiala, Punjab, India. He received the Most Outstanding Researcher award in the field of Mathematics from Carrer 360 Academy. He is also the recipient of the International 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 Publishers. He also serves as an advisory board member of the Universal Scientific Education and Research Network (USERN). He is a research fellow of INTI International University, Malaysia. He is ranked in the world’s top 2% scientist list and rank #1 in India and World Rank #163 published by Stanford University in the consecutive years from 2020–2024. 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 540 papers (over 520 are SCI) published in refereed international journals including IEEE Transactions, Elsevier, Springer, etc. His Google citations are over 28,300 with H-index-93. He is one of the leading researchers in the world related to the reliability, MCDM and soft computing approaches. 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 Alexandria Engineering Journal, Journal of Industrial & Management Optimization, CAAI Transactions on Intelligence Technology, etc.