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This book is intended to help management and other interested parties such as engineers, to understand the state of the art when it comes to the intersection between AI and Industry 4.0 and get them to realise the huge possibilities which can be unleashed by the intersection of these two fields.
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.- Affect 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.