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            Artificial Intelligence in Manufacturing

            Enabling Intelligent, Flexible and Cost-Effective Production Through AI

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            Contributor(s)
            Soldatos, John (editor)
            Language
            English
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            Abstract
            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.
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/197094
            Keywords
            Industry 4.0; Industry 5.0; Reinforcement Learning; Intelligent Agents; Explainable AI; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJK Communications engineering / telecommunications; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence; thema EDItEUR::U Computing and Information Technology::UN Databases; thema EDItEUR::U Computing and Information Technology; thema EDItEUR::K Economics, Finance, Business and Management::KJ Business and Management::KJQ Business mathematics and systems
            DOI
            10.1007/978-3-031-46452-2
            ISBN
            9783031464522, 9783031464515
            Publisher
            Springer Nature
            Publisher website
            http://www.springernature.com/oabooks
            Publication date and place
            Cham, 2024
            Imprint
            Springer Nature Switzerland
            Pages
            505
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            Credits


            • logo Investir l'avenirInvestir l'avenir
            • logo MESRIMESRI
            • logo EUEuropean Union
              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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