Buch, Englisch, 416 Seiten, Format (B × H): 156 mm x 234 mm
Reihe: River Publishers Series in Mathematical, Statistical and Computational Modelling for Engineering
Challenges and Applications
Buch, Englisch, 416 Seiten, Format (B × H): 156 mm x 234 mm
Reihe: River Publishers Series in Mathematical, Statistical and Computational Modelling for Engineering
ISBN: 978-87-438-1232-6
Verlag: River Publishers
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.
Zielgruppe
Academic, Postgraduate, and Professional Practice & Development
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Chapter 1: Reliability Meets Sustainability: Decision-making Strategies for Future-proof Energy Systems Chapter 2: Analysis of equity-linked death benefits using the exponential Levy process Chapter 3: Patient Rehospitalization Forecasting by Optimizing the Reliability of Predictive Mode Chapter 4: A Copula Model-based Optimization Approach for Reliability Analysis in Complex Systems Chapter 5: Computational Intelligence for Identifying Rainfall Patterns and Engine Prognosis Chapter 6: Neuro-symbolic Systems Applied to Prognostics and Health Management: A Brief Survey Chapter 7: A Novel Approach for More Accurate Prediction of Stock Market Volatility Chapter 8: Recent Perspectives on Anomaly Detection in Multivariate Time Series for Predictive Maintenance in Industry 4.0 Chapter 9: Preventive Maintenance Optimization of Water Pump Based on Genetic Algorithm Chapter 10: Intuitionistic Fuzzy EOQ Model with Time and Reliability Dependent Demand and Backordering Chapter 11: Optimization of Imperfect Maintenance: Emerging Theories and Adaptive Practices Chapter 12: Enhancing Workplace Mental Health: Reliable and Sustainable Therapy Predictions using Machine Learning Chapter 13: Use of the Markov Approach for RAM Analysis of a Parallel System of Non-identical Units
