000			04110nam a22003015i 4500
001			401994
003			DE-He213
005			20240514120038.0
007			cr nn 008mamaa
008			240208s2024 sz | o |||| 0|eng d
020			_a9783031464522
024	7		_a10.1007/978-3-031-46452-2 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTK5101-5105.9 _b2024 EB
245	0	0	_aArtificial Intelligence in Manufacturing : _bEnabling Intelligent, Flexible and Cost-Effective Production Through AI _cedited by John Soldatos
250			_a1st ed. 2024.
264		1	_aCham _bSpringer International Publishing _c2024
300			_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
505	0		_aIntroduction -- 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.
506	0		_aOpen Access
520			_aThis 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.
942			_2lcc _cLE
988			_aSpringer_Engineering_2024
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-46452-2 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
999			_c401994 _d401994