Artificial Intelligence in Manufacturing : Enabling Intelligent, Flexible and Cost-Effective Production Through AI / / edited by John Soldatos

• Pubblicazione: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
• Edizione: 1st ed. 2024.
• Descrizione fisica: 1 online resource (XXVII, 505 p. 175 illus., 153 illus. in color.)
• Disciplina: 621.382
• Soggetto topico: Telecommunication; Artificial intelligence; Big data; Blockchains (Databases); Business information services; Communications Engineering, Networks; Artificial Intelligence; Big Data; Blockchain; IT in Business
• Persona (resp. second.): SoldatosJohn
• Nota di contenuto: 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.
• Sommario/riassunto: 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.
• Titolo autorizzato: Artificial Intelligence in Manufacturing
• ISBN: 3-031-46452-4
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910829580903321
• Lo trovi qui: Univ. Federico II