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240301 ||| eng |
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|a 9783031464522
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| 100 |
1 |
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|a Soldatos, John
|e [editor]
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| 245 |
0 |
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|a Artificial Intelligence in Manufacturing
|h Elektronische Ressource
|b Enabling Intelligent, Flexible and Cost-Effective Production Through AI
|c edited by John Soldatos
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| 250 |
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|a 1st ed. 2024
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| 260 |
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|a Cham
|b Springer Nature Switzerland
|c 2024, 2024
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| 300 |
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|a XXVII, 505 p. 175 illus., 153 illus. in color
|b online resource
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| 505 |
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|a 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
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| 653 |
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|a Big data
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| 653 |
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|a Artificial Intelligence
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| 653 |
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|a Blockchains (Databases)
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| 653 |
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|a IT in Business
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| 653 |
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|a Telecommunication
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| 653 |
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|a Artificial intelligence
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| 653 |
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|a Communications Engineering, Networks
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| 653 |
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|a Blockchain
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| 653 |
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|a Big Data
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| 653 |
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|a Business information services
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| 041 |
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|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 028 |
5 |
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|a 10.1007/978-3-031-46452-2
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| 856 |
4 |
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|u https://doi.org/10.1007/978-3-031-46452-2?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 621.382
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| 520 |
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|a 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) and emerging trustworthy and human-centered manufacturing systems (Industry 5.0). From a technology perspective, the book addresses a wide range of AI paradigms such as deep learning, reinforcement learning, active learning, agent-based systems, explainable AI, industrial robots, and AI-based digital twins. Emphasis is put on system architectures and technologies that foster human-AI collaboration based on trusted interactions between workers and AI systems. From a manufacturing applications perspective, the book illustrates the deployment of these AI paradigms in a variety of use cases spanning production planning, quality control, anomaly detection, metrology, workers’ training, supply chain management, as well as various production optimization scenarios. This is an open access book
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