Investigation of a Fully-automated Manufacturing Environment Realized through a Flexible Logistic System

Subject Areas :

Jan-Hinrich Kämper ¹ , Arne Stasch ²

1 - Department of Computing Science, Carl von Ossietzky University, Oldenburg, Germany
2 - OFFIS Institute for Information Technology Oldenburg, Oldenburg, Germany

Received: 2022-06-10 Accepted : 2022-08-01 Published : 2022-05-15

Keywords: AGV, MFS, Flexible Logistic System, In-house transportation,

Abstract :

Modern industrial production and transportation systems require agile material handling systems. Changing requirements demand flexibility in transportation layout and control systems that are adaptable to the actual needs. Decentralized control systems promise complexity reduction and dependability while centralized approaches improve planning and allow general optimization. By using the use case of a cross-docking logistic system the paper describes how this approach can be combined and implemented by using an agent-based control system on a decentralized lightweight microcontroller infrastructure. The scenario applies to manufacturing environments with modularized assembly lines. These modules are connected by different transport units which merge into an intelligent infrastructure including AGVs, conveyors, and storage.

References:

[1] Gunasekaran, A. 2001. Agile Manufacturing: The 21^st Century Competitive Strategy ultiagent systems: a modern approach to distribute artificial intelligence. Elsevier.

[2] Weiss, G. 1999. Multiagent systems: a modern approach to distribute artificial intelligence. MIT press.

[3] Günthner, W. 2010. Internet der Dinge in der Intralogistik. Springer, Heidelberg.

[4] D’Andrea, R. 2012. Guest editorial: A revolution in the warehouse: A retrospective on KIVA systems and the grand challenges ahead. IEEE Transactions on Automation Science and Engineering. 9(4):638-639.

[5] Kamagaew, A. 2011. Concept of cellular transport systems in facility logistics. 5th International Conference on Automation, Robotics and Applications (ICARA), IEEE.

[6] Seibold, Z. 2013. Layout-optimized sorting of goods with decentralized controlled conveying modules. Systems Conference (SysCon), IEEE.

[7] Horbach, S., Ackermann, J. Müller, E. and Schütze, J. Building blocks for adaptable factory systems. Robotics and Computer-Integrated Manufacturing. 27(4): 735-740. 2011.

[8] Bellifemine, F., Poggi, A. and Rimassa, G. 1999. JADE–A FIPA-compliant agent framework. Proceedings of The Practical Application of intelligent Agents and Multi-Agent Technology. 99: 97-108.

[9] Chou, Y., Ko, D. and Cheng, H. 2010. An embeddable mobile agent platform supporting runtime code mobility, interaction and coordination of mobile agents and host systems. Information and Software Technology. 52(2):185-196.

[10] Ogston, E., Overeinder, B. Van Steen, M. and Brazier, F. 2003. A method for decentralized clustering in large multi-agent systems. Proceedings of the second international joint conference on Autonomous agents and multiagent systems.

[11] Marcolino, L. 2013. Diversity beats strength? Towards forming a powerful team. 15^th International Workshop on Coordination, Organizations, Institutions and Norms (COIN).

[12] Koestler, A. 1972. The Rules of the Game: Beyond Atomism and Holism–The concept of the holon 1. Taylor & Francis.

[13] Fletcher, M., and Deen, M. 2001. Fault‐tolerant holonic manufacturing systems. Concurrency and computation: practice and experience, 13(1):43-70.

[14] Rodriguez, S., Hilaire,V., Gaud, N., Galland, S. and   Koukam, A. 2011. Holonic multi-agent systems. Self-organising Software. Springer, Heidelberg.

[15] Ten Hompel, M., Nettstraeter, A., Feldhorst, S. and Schier, A. 2011. Engineering of Modular Material Flow Systems in the Internet of Things. Automatisierungstechnik. 59(4):248-256.

[16] Lee, E. 2008. Cyber Physical Systems: Design Challenges. 11^th IEEE Symposium on Object Oriented Real-Time Distributed Computing (ISORC).

[17] Hill, J.L. and Culler, D.E. Mica: 2002. A wireless platform for deeply embedded networks. IEEE Micro, 22(6): 12 - 24.

[18] Stasch, A. and Hahn, A. 2013. Towards a Multi-Agent Platform for Cyber-physical Systems based on Low-power Microcontroller for Automated Intralogistics. Proceedings of the 10^th International Conference on Informatics in Control, Automation and Robotics.

[19] Heinecke, H. Schnelle, K., Fennel, H. and Bortolazzi, J. 2004. AUTomotive Open System ARchitecture-an industry-wide initiative to manage the complexity of emerging automotive E/E-architectures. Convergence International Congress & Exposition on Transportation Electronics, Detroit, Michigan, United States.

[20] Nicol, R.C. and OʼBrien, P.D. 1998. FIPA-towards a standard for software agents. BT Technology Journal. 16:51–59.

[21] Lewandowski, M. 2013. Agent-based Control for Material Handling Systems in In-House Logistics. European Conference on Smart Objects, Systems and Technologies.

[22] Hart, P. E., Nilsson, N. J. and Raphael, B.  1968. A Formal Basis for the Heuristic Determination of Minimum Cost Paths. IEEE Transactions on Systems Science and Cybernetics. 4(2): 100–107.

[23] Lee, C. Y. 1961. An Algorithm for Path Connections and Its Applications. IRE Transactions on Electronic Computers, EC-10 (2): 346–365.