Artificial Intelligence in Manufacturing Enabling Intelligent, Flexible and Cost-Effective Production Through AI
This open access book presents a rich set of innovative solutions for artificial intelligence (AI) in manufacturing. The various chapters of the book provide a broad coverage of AI systems for state of the art flexible production lines including both cyber-physical production systems (Industry 4.0)...
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| Format: | eBook |
| Language: | English |
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Cham
Springer Nature Switzerland
2024, 2024
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| Edition: | 1st ed. 2024 |
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| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Introduction
- Part I Architectures and Knowledge Modelling for AI in Manufacturing
- Reference Architecture for AI-based Industry 5.0 Applications
- Designing a Marketplace to Exchange AI Models for Industry 4.0
- Domain Ontology Enrichment through Human-AI Interaction
- Survey of Knowledge Graphs in Industrial Settings
- From Knowledge to Wisdom: Leveraging Semantic Representations via Knowledge Graph Embeddings
- Advancing high value-added networked production through Decentralized Technical Intelligence
- Part II AI-based Digital Twins for Manufacturing Applications
- Digital-Twin enabled framework for training and deploying AI agents for production scheduling
- Digital Twin for Human Machine Interaction
- Learning-based Collaborative Digital Twins
- A Manufacturing Digital Twin Framework
- Part III Agent based Approaches for AI in Manufacturing
- Reinforcement Learning based approaches in manufacturing environments
- A participatory modelling approach to Agents in Industry using AAS
- 4.0 Holonic Multi-Agent Testbed Enabling Shared Production
- Application of a Multi agent system on production and scheduling optimization
- Integrating Knowledge to Conversational Agents for Worker Upskilling
- Part IV Trusted AI for Industry 5.0 Applications
- Wearable sensor-based human activity recognition for worker safety in manufacturing line
- Object detection for human-robot interaction and worker assistance systems
- Application of autoML, XAI and differential privacy method into manufacturing
- Anomaly Detection in Manufacturing
- Towards Industry 5.0 by incorporation of Trustworthy and Human-Centric approaches
- How AI changes human roles in Industry 5.0-enabled environments: Human in the AI loop via xAI and Active Learning for Manufacturing Quality Control
- Multi-Stakeholder Perspective on Human-AI Collaboration in Industry 5.0
- Conclusion