Artificial Intelligence in Manufacturing
portes grátis
Artificial Intelligence in Manufacturing
Enabling Intelligent, Flexible and Cost-Effective Production Through AI
Soldatos, John
Springer International Publishing AG
02/2024
505
Mole
Inglês
9783031464546
15 a 20 dias
Descrição não disponível.
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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Industry 4.0;Open access;Industry 5.0;Reinforcement Learning;Intelligent Agents;Explainable AI;Open Access
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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