The MAS4AI framework for human-centered agile and smart manufacturing

Frontiers in Artificial Intelligence

Artificial Intelligence

William Motsch¹  Aleksandr Sidorenko¹  Achim Wagner¹  Nikolaos Nikolakis²  Kosmas Alexopoulos²  Michael van Bekkum³ 

[1] Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, Kaiserslautern, Germany;Laboratory for Manufacturing Systems and Automation, Department of Mechanical Engineering and Aeronautics, University of Patras, Patras, Greece;Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek, The Hague, Netherlands;

关键词: Artificial Intelligence;    Asset Administration Shell;    human-centered AI;    multi-agent system;    Human Digital Holon;    self-configuration;    shared assembly;   

DOI  :  10.3389/frai.2023.1241522

 received in 2023-06-16, accepted in 2023-09-06,  发布年份 2023

来源: Frontiers

【 摘 要 】

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.

【 授权许可】

Unknown   
Copyright © 2023 Sidorenko, Motsch, van Bekkum, Nikolakis, Alexopoulos and Wagner.