Multiagent systems for distributed production

Multiagent systems for distributed production

Paper in proceedings outside WoS and Scopus

Manufacturing companies today face a dynamic environment in which economic, technological, and customer trends are changing rapidly. It is requiring increased demands for flexibility and agility in production management and planning. To handle the growing complexity of systems, we need new methods where decentralization is playing an important role. In this context, the challenge is to develop an innovative, agile, and reconfigurable architecture for distributed production management using new paradigms in response to market demands. The use of multi-agent systems that reflect these demands in their design can be a suitable alternative to traditional centralized production management. In this document, we present a theoretical knowledge base of intelligent manufacturing systems and briefly introduce the implementation of such a production management model.

Manufacturing companies today face a dynamic environment in which economic, technological, and customer trends are changing rapidly. It is requiring increased demands for flexibility and agility in production management and planning. To handle the growing complexity of systems, we need new methods where decentralization is playing an important role. In this context, the challenge is to develop an innovative, agile, and reconfigurable architecture for distributed production management using new paradigms in response to market demands. The use of multi-agent systems that reflect these demands in their design can be a suitable alternative to traditional centralized production management. In this document, we present a theoretical knowledge base of intelligent manufacturing systems and briefly introduce the implementation of such a production management model.

scheduling, planning, C# algorithm, multi-agent approach, optimization, simulation, Industry 4.0

scheduling, planning, C# algorithm, multi-agent approach, optimization, simulation, Industry 4.0

ŽIAČIK, M.; KACZMARCZYK, V.

2024

26.04.2023

Brno University of Technology, Faculty of Electrical Engineering and Communication

Brno

ISBN 978-80-214-6153

PROCEEDINGS I OF THE 29TH STUDENT EEICT 2023 General papers

160

163

4

https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2023_sbornik_1.pdf