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The MAS4AI framework for human-centered agile and smart manufacturing
Volatility and uncertainty of today's value chains along with the market's demands for low-batch customized products mandate production systems to become smarter and more resilient, dynamically and even autonomously adapting to both external and internal disturbances. Such resilient behavi...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10568179/ https://www.ncbi.nlm.nih.gov/pubmed/37841235 http://dx.doi.org/10.3389/frai.2023.1241522 |
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author | Sidorenko, Aleksandr Motsch, William van Bekkum, Michael Nikolakis, Nikolaos Alexopoulos, Kosmas Wagner, Achim |
author_facet | Sidorenko, Aleksandr Motsch, William van Bekkum, Michael Nikolakis, Nikolaos Alexopoulos, Kosmas Wagner, Achim |
author_sort | Sidorenko, Aleksandr |
collection | PubMed |
description | Volatility and uncertainty of today's value chains along with the market's demands for low-batch customized products mandate production systems to become smarter and more resilient, dynamically and even autonomously adapting to both external and internal disturbances. Such resilient behavior can be partially enabled by highly interconnected Cyber-Physical Production Systems (CPPS) incorporating advanced Artificial Intelligence (AI) technologies. Multi-agent solutions can provide better planning and control, improving flexibility and responsiveness in production systems. Small modular parts can autonomously take intelligent decisions and react to local events. The main goal of decentralization and interconnectivity is to enable autonomous and cooperative decision-making. Nevertheless, a more efficient orchestration of various AI components and deeper human integration are required. In addition, global behaviors of coalitions of autonomous agents are not easily comprehensible by workers. Furthermore, it is challenging to implement an Industry 4.0 paradigm where a human should be in charge of decision-making and execution. This paper discusses a Multi-Agent System (MAS) where several software agents cooperate with smart workers to enable a dynamic and reconfigurable production paradigm. Asset Administration Shell (AAS) submodels hold smart workers' descriptions in machine-readable format, serving as an integration layer between various system's components. The self-description capability of the AAS supports the system's adaptability and self-configuration. The proposed concept supports the plug-and-produce functionality of the production modules and improves human-machine integration in the shared assembly tasks. |
format | Online Article Text |
id | pubmed-10568179 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-105681792023-10-13 The MAS4AI framework for human-centered agile and smart manufacturing Sidorenko, Aleksandr Motsch, William van Bekkum, Michael Nikolakis, Nikolaos Alexopoulos, Kosmas Wagner, Achim Front Artif Intell Artificial Intelligence Volatility and uncertainty of today's value chains along with the market's demands for low-batch customized products mandate production systems to become smarter and more resilient, dynamically and even autonomously adapting to both external and internal disturbances. Such resilient behavior can be partially enabled by highly interconnected Cyber-Physical Production Systems (CPPS) incorporating advanced Artificial Intelligence (AI) technologies. Multi-agent solutions can provide better planning and control, improving flexibility and responsiveness in production systems. Small modular parts can autonomously take intelligent decisions and react to local events. The main goal of decentralization and interconnectivity is to enable autonomous and cooperative decision-making. Nevertheless, a more efficient orchestration of various AI components and deeper human integration are required. In addition, global behaviors of coalitions of autonomous agents are not easily comprehensible by workers. Furthermore, it is challenging to implement an Industry 4.0 paradigm where a human should be in charge of decision-making and execution. This paper discusses a Multi-Agent System (MAS) where several software agents cooperate with smart workers to enable a dynamic and reconfigurable production paradigm. Asset Administration Shell (AAS) submodels hold smart workers' descriptions in machine-readable format, serving as an integration layer between various system's components. The self-description capability of the AAS supports the system's adaptability and self-configuration. The proposed concept supports the plug-and-produce functionality of the production modules and improves human-machine integration in the shared assembly tasks. Frontiers Media S.A. 2023-09-28 /pmc/articles/PMC10568179/ /pubmed/37841235 http://dx.doi.org/10.3389/frai.2023.1241522 Text en Copyright © 2023 Sidorenko, Motsch, van Bekkum, Nikolakis, Alexopoulos and Wagner. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Artificial Intelligence Sidorenko, Aleksandr Motsch, William van Bekkum, Michael Nikolakis, Nikolaos Alexopoulos, Kosmas Wagner, Achim The MAS4AI framework for human-centered agile and smart manufacturing |
title | The MAS4AI framework for human-centered agile and smart manufacturing |
title_full | The MAS4AI framework for human-centered agile and smart manufacturing |
title_fullStr | The MAS4AI framework for human-centered agile and smart manufacturing |
title_full_unstemmed | The MAS4AI framework for human-centered agile and smart manufacturing |
title_short | The MAS4AI framework for human-centered agile and smart manufacturing |
title_sort | mas4ai framework for human-centered agile and smart manufacturing |
topic | Artificial Intelligence |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10568179/ https://www.ncbi.nlm.nih.gov/pubmed/37841235 http://dx.doi.org/10.3389/frai.2023.1241522 |
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