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Performance evaluation of skill-based order-assignment in production environments with multi-agent systems

  • The fourth industrial revolution introduces disruptive technologies to production environments. One of these technologies are multi-agent systems (MASs), where agents virtualize machines. However, the agent's actual performances in production environments can hardly be estimated as most research has been focusing on isolated projects and specific scenarios. We address this gap by implementing a highly connected and configurable reference model with quantifiable key performance indicators (KPIs) for production scheduling and routing in single-piece workflows. Furthermore, we propose an algorithm to optimize the search of extrema in highly connected distributed systems. The benefits, limits, and drawbacks of MASs and their performances are evaluated extensively by event-based simulations against the introduced model, which acts as a benchmark. Even though the performance of the proposed MAS is, on average, slightly lower than the reference system, the increased flexibility allows it to find new solutions and deliver improved factory-planning outcomes. Our MAS shows an emerging behavior by using flexible production techniques to correct errors and compensate for bottlenecks. This increased flexibility offers substantial improvement potential. The general model in this paper allows the transfer of the results to estimate real systems or other models.

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Metadaten
Author:Sebastian BraunORCiD, Chi-Tsun Cheng, Steve Dowey, Jörg WollertORCiD
DOI:https://doi.org/10.1109/JESTIE.2021.3108524
ISSN:2687-9735
Parent Title (English):IEEE Journal of Emerging and Selected Topics in Industrial Electronics
Publisher:IEEE
Place of publication:New York
Document Type:Article
Language:English
Year of Completion:2021
Date of first Publication:2021/08/30
Date of the Publication (Server):2021/09/14
Tag:cyber-physical production systems; digital factory; event-based simulation; industrial agents; multi-agent systems
Issue:Early Access
Link:https://doi.org/10.1109/JESTIE.2021.3108524
Zugriffsart:campus
Institutes:FH Aachen / Fachbereich Maschinenbau und Mechatronik
FH Aachen / MASKOR Institut für Mobile Autonome Systeme und Kognitive Robotik
collections:Verlag / IEEE