Artificial Intelligence in Industry 4.0

Part I: Managing the Industry 4.0 revolution.- Implementing Industry 4.0 -The Need for a Holistic Approach.- Motivation in a business company using technology-based communication.- Decision Support in Everyday Business using Self-Enforcing Networks.- Approaches for Cognitive Assistance in Industry 4.0.- Part II: Modelling for Industry 4.0.- Modelling and Simulation in Industry 4.0.- Homogenization algorithm based on incremental L2-discrepancy filtering for data-driven modelling.- Linking Industry 4.0, Learning Factory and Simulation: testbeds and proof-of-concept experiments.- Part III: Machine Learning in Industry 4.0.- Intelligent Digital Twin system in the semiconductors manufacturing industry.- Automatic defect recognition in nonwovens using images and metadata analysis - a deep learning approach.- MIRAI: A Modifiable, Interpretable, and Rational AI decision support system.- Multi-Agent Reinforcement Learning for the Energy Optimization of Cyber-Physical Production Systems.- A ect ofartificial intelligence technologies and digitalisation on jurisprudence and education.- Part IV: Agents in Industry 4.0.- Approach for model driven development of multi agent systems for ambient intelligence.- Designing trust in highly automated virtual assistants : A taxonomy of levels of autonomy.- Introducing the concept of "digital-agent signatures": How SSI can be expanded for the needs of Industry 4.0.