International Congress and Workshop on Industrial AI and eMaintenance 2025
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Beschreibung
This proceedings volume will document the state-of-the-art research, case studies, and technological advancements in Industrial Artificial Intelligence and intelligent asset management. The content will be relevant to industrial and academic audiences, covering topics such as eMaintenance, Industry 5.0, predictive analytics, intelligent asset management, cybersecurity, and advanced digitalisation solutions. By presenting both academic and practical insights, the volume aims to bridge the gap between theory and application in managing industrial assets. The primary readership includes professionals, researchers, and students interested in the applications of AI for optimizing industrial operations and maintenance.
This proceedings volume will document the state-of-the-art research, case studies, and technological advancements in Industrial Artificial Intelligence and intelligent asset management. The content will be relevant to industrial and academic audiences, covering topics such as eMaintenance, Industry 5.0, predictive analytics, intelligent asset management, cybersecurity, and advanced digitalisation solutions. By presenting both academic and practical insights, the volume aims to bridge the gap between theory and application in managing industrial assets. The primary readership includes professionals, researchers, and students interested in the applications of AI for optimizing industrial operations and maintenance.
Covers industries such as aerospace, railways, mining, construction, and the process industry Encourages discussions between researchers and industrial practitioners Demonstrates the opportunities and challenges of applying AI to industrial operations and maintenance
Autor*in
Ravdeep Kour
Themen in »International Congress and Workshop on Industrial AI and eMaintenance 2025«
Industrial AI & Digitalisation Reliability Availability Maintainability & Safety (RAMS) Intelligent Asset Management Digital Twin Human System Interaction Condition monitoring