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

Inhalt

A Performability Optimization Framework for Driverless and Unattended Mainline Systems.- Deep Reinforcement Learning for Maintenance Planning in Weibull Distributed Fleet Systems.- Synthetic MQTT Traffic Generation for Real-Time IoT Security Threat Analysis with Artificial Intelligence.- Balancing Cost, Risk, and Performance in Railway Asset Management: An Enhanced ORIE Approach.- Effective Gravel Road Maintenance: Insights from Condition Assessment by Integrating Data Sources.- Fundamentals of RCM and their application in railway infrastructure asset management.- On the development and use of hybrid models in aircraft component and sub-system health monitoring.- Development of fault diagnostic support Application for railway sleepers.- Design and Prognosis of CanSat Maneuver Systems using Machine Learning.- Review of Neuroergonomics approaches for evaluating mental workload.- Making correct maintenance decisions - A content analysis of Reliability-Centered Maintenance (RCM).- Life Cycle Management of Railway Infrastructure - A Case Study at the Swedish Iron Ore Line.- A Generative AI Framework for Smart Maintenance: Utilizing RAG Systems and LLMs to Assist Manufacturing Operations.- Data-driven decision support tool for maintenance of capital-intensive mining equipment.- Enhancing Railway Infrastructure Resilience: Towards A Hybrid Multi-physics and Data-Driven Approach for Condition Monitoring.- European Union Data act enabling IoT data sharing for creation of new services and software products.- EEG Signal Analysis in Golf Putting: Correlating Brain Activity with Putting Success.- Support for daily decisions of safety on scaffolding at construction sites through applied AI.- Using Data from Multiple Wayside Train Monitoring Systems to Detect and Estimate the Size of Wheel Flats on Railway Vehicles.