Erhältlich:
Nicht auf Lager
Buch (Hardcover): Fachbuch
Data-Driven Methods for Reliability and Safety Engineering: Applications in Industrial Systems
Leveraging AI, Machine Learning, and Advanced Analytics to Enhance Risk Assessment, Decision-Making, and System Performance
Produkt bewerten
Verlag:
Springer Verlag Unsere-Artikel-Nr.: P35034480
EAN: 9783032228727
Erhältlich:
Nicht auf Lager
Zustellung: Di, 01.09.2026
Versand: Kostenlos
-16.8 %
CHF 238.–
CHF 198.–
Beschreibung
This book provides a comprehensive guide to using data-driven methods in reliability and safety engineering for industrial systems. It explores how modern technologies like data analytics, machine learning, and artificial intelligence can enhance decision-making, predict failures, and improve system resilience. In an era of increasingly complex industrial systems, traditional methods often fail to address reliability and safety challenges. This book highlights how integrating data-driven techniques can optimize system performance, reduce risks, and enhance safety outcomes. Key topics include predictive maintenance, risk assessment, AI integration, and the challenges of implementing these technologies in real-world environments. Case studies across industries like energy and manufacturing illustrate the practical applications of these methods. This book is aimed at professionals in reliability engineering, safety, risk management, and industrial systems, as well as researchers and students seeking to understand the role of data-driven methods in modern engineering practices.
Spezifikationen
Sprache
- Englisch
Autor
- Mohammad Yazdi
- Hong-Zhong Huang
- He Li
- Ke Feng
Zielgruppe
- Research
Erscheinungsjahr
- 2026
Format
- Buch (Hardcover)
Anzahl Seiten
- 728