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An agent-based architecture for production scheduling in dynamic job-shop manufacturing system

Eine agentenbasierte Architektur für Produktionsplanung in einem dynamischen Auftragsfertigungssystem
  • Om Ji Shukla

    Om Ji Shukla is pursuing his PhD in the Department of Mechanical Engineering, Malaviya National Institute of Technology Jaipur, Rajasthan, India. His research interests include multi-agent systems, artificial intelligence in manufacturing, operations management and lean manufacturing.

    , Gunjan Soni

    Gunjan Soni is an Assistant Professor in the Department of Mechanical Engineering, Malaviya National Institute of Technology Jaipur, Rajasthan, India. His research interests include agent-based modelling, supply chain risk management, supply chain quality and artificial intelligence in manufacturing. He is currently interested in developing multi-agent-based models for manufacturing systems. His other engagements are focused on risk mitigation in supply chains and quality engineering for perishable supply chains.

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    , Rajesh Kumar

    Rajesh Kumar is an Associate Professor in the Department of Electrical Engineering, Malaviya National Institute of Technology Jaipur, Rajasthan, India. His research interests include computational intelligence, intelligent systems, machine learning, power conversion and management, smart grids and robotics. He has been at the National University of Singapore as post doctorate Research Fellow. Current activities include development of bio-inspired algorithms, system prediction models, smart power networks, medical assistive systems and data analysis.

    and Sujil A

    Sujil A. is pursuing his PhD in the Department of Electrical Engineering, Malaviya National Institute of Technology Jaipur, Rajasthan, India. His research interests include smart grids, load forecasting, DSM, multi-agent systems and self-healing of power systems.

Abstract

In a highly competitive environment, effective production is one of the key issues which can be addressed by efficient production planning and scheduling in the manufacturing system. This paper develops an agent-based architecture which enables integration of production planning and scheduling. In addition, this architecture will facilitate real time production scheduling as well as provide a multi-agent system (MAS) platform on which multiple agents will interact to each other. A case study of job-shop manufacturing system (JMS) has been considered in this paper for implementing the concept of MAS. The modeling of JMS has been created in SimEvents which integrates an agent-based architecture developed by Stateflow to transform into dynamic JMS. Finally, the agent-based architecture is evaluated using utilization of each machine in the shop floor with respect to time.

Zusammenfassung

In hart umkämpften Geschäftsumfeldern ist die effektive Produktion ein Schlüsselfaktor, der durch effiziente Produktions- und Zeitplanung im Fertigungssystem bestimmt wird. Dieser Beitrag entwickelt eine agentenbasierte Architektur, die beides integriert, eine Produktions- als auch Zeitplanung. Weiterhin erlaubt diese Architektur eine Zeitplanung in Echtzeit und stellt ein Multiagentensystem (MAS) bereit, auf dessen Plattform mehrere Agenten interagieren können. Wir betrachten eine Fallstudie eines Auftragsfertigungssystems (job-shop manufacturing system, JMS) für die Implementierung des MAS-Konzepts. Die Modellierung des JMS ist in SimEvents realisiert worden, wobei eine auf Stateflow beruhende agentenbasierte Architektur die Dynamik des JMS ermöglicht. Zum Schluss evaluieren wir die agentenbasierte Architektur anhand der zeitlichen Auslastung aller Maschinen der Fertigungsanlage.

About the authors

Om Ji Shukla

Om Ji Shukla is pursuing his PhD in the Department of Mechanical Engineering, Malaviya National Institute of Technology Jaipur, Rajasthan, India. His research interests include multi-agent systems, artificial intelligence in manufacturing, operations management and lean manufacturing.

Gunjan Soni

Gunjan Soni is an Assistant Professor in the Department of Mechanical Engineering, Malaviya National Institute of Technology Jaipur, Rajasthan, India. His research interests include agent-based modelling, supply chain risk management, supply chain quality and artificial intelligence in manufacturing. He is currently interested in developing multi-agent-based models for manufacturing systems. His other engagements are focused on risk mitigation in supply chains and quality engineering for perishable supply chains.

Rajesh Kumar

Rajesh Kumar is an Associate Professor in the Department of Electrical Engineering, Malaviya National Institute of Technology Jaipur, Rajasthan, India. His research interests include computational intelligence, intelligent systems, machine learning, power conversion and management, smart grids and robotics. He has been at the National University of Singapore as post doctorate Research Fellow. Current activities include development of bio-inspired algorithms, system prediction models, smart power networks, medical assistive systems and data analysis.

Sujil A

Sujil A. is pursuing his PhD in the Department of Electrical Engineering, Malaviya National Institute of Technology Jaipur, Rajasthan, India. His research interests include smart grids, load forecasting, DSM, multi-agent systems and self-healing of power systems.

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Received: 2018-1-22
Accepted: 2018-1-29
Published Online: 2018-6-5
Published in Print: 2018-6-26

© 2018 Walter de Gruyter GmbH, Berlin/Boston

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