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IJAT Vol.14 No.5 pp. 713-722
doi: 10.20965/ijat.2020.p0713
(2020)

Paper:

Automatic Construction of Virtual Supply Chain as Multi-Agent System Using Enterprise E-Catalogues

Tatsushi Nishi*,†, Michiko Matsuda**, Mao Hasegawa***, Roghayyeh Alizadeh***, Ziang Liu***, and Takuto Terunuma***

*Okayama University
3-1-1 Tsushima-naka, Kita-ku, Okayama City, Okayama 700-8530, Japan

Corresponding author

**Japanese Standard Association, Tokyo, Japan

***Osaka University, Toyonaka, Japan

Received:
March 11, 2020
Accepted:
May 25, 2020
Published:
September 5, 2020
Keywords:
smart manufacturing, supply chain, digital transformation, multi-agent simulation, enterprise agents
Abstract

In Industry 4.0, a network of enterprises and factories is constructed collaboratively and dynamically according to the cyber physical system (CPS) paradigm. It is necessary to build smart supply chains according to this concept. A network of component enterprises in a supply chain would be modeled as a virtual supply chain in the cyber world. From the viewpoint of Industry 4.0, virtualizing a supply chain is the foundation for constructing a CPS for a supply chain. The virtualization of a supply chain makes it easier for companies to study their integrating and expanding opportunities. By using this CPS, comprehensive and autonomous optimization of the supply chain can be achieved. This virtual supply chain can be used to simulate the planning phase with negotiation, as well as the production phase. In this paper, instead of specific mathematical modeling for each supply chain, a general configuration method of a virtual supply chain is proposed. The configuration method of a supply chain model is proposed as a virtual supply chain using enterprise e-catalogues. A virtual supply chain is constructed as a multi-agent system, which is connections of software agents that are automatically created from each selected enterprise model in the e-catalogues. Three types of component enterprise models are provided: manufacturer model, part/material supplier model, and retailer model. Modeling templates for these three types of enterprises are prepared, and each template is a nominal model in terms of enterprise’s behavior. Specific component-enterprise models are prepared by filling the appropriate template. Each component enterprise agent is implemented using the enterprise model selected from the catalogues. Manufacturer, retailer, and supplier e-catalogues, as well as an automatic construction system of a virtual supply chain, are implemented. Methods for developing templates for the manufacturer, retailer and supplier were provided, and the construction system for specific enterprise models (as e-catalogues) is implemented as a trial.

Cite this article as:
T. Nishi, M. Matsuda, M. Hasegawa, R. Alizadeh, Z. Liu, and T. Terunuma, “Automatic Construction of Virtual Supply Chain as Multi-Agent System Using Enterprise E-Catalogues,” Int. J. Automation Technol., Vol.14 No.5, pp. 713-722, 2020.
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References
  1. [1] G. W. Tan, M. J. Shaw, and B. Fulkerson, “Web-based supply chain management,” Inf. Syst. Front., Vol.2, No.1, pp. 41-55, 2000.
  2. [2] A. Chandrashekar and P. B. Schary, “Toward the virtual supply chain: the convergence of IT and organiation,” Int. J. Logist. Manag., Vol.10, No.2, pp. 27-40, 1999.
  3. [3] V. Manthou, M. Vlachopoulou, and D. Folinas, “Virtual e-chain (VeC) model for supply chain collaboration,” Int. J. Prod. Econ., Vol.87, No.3, pp. 241-250, 2004.
  4. [4] A. Gunasekaran and E. W. T. Ngai, “Virtual supply-chain management,” Prod. Plan. Cont., Vol.15, No.6, pp. 584-595, 2004.
  5. [5] E. T. G. Wang, J. C. F. Tai, and H.-L. Wei, “A virtual integration theory of improved supply-chain performance,” J. Manag. Inf. Syst., Vol.23, No.2, pp. 41-64, 2006.
  6. [6] W. Y. C. Wang and H. K. Chan, “Virtual organization for supply chain integration: Two cases in the textile and fashion retailing industry,” Int. J. Prod. Econ., Vol.127, No.2, pp. 333-342, 2010.
  7. [7] C. N. Verdouw, J. Wolfert, A. J. M. Beulens, and A. Rialland, “Virtualization of food supply chains with the internet of things,” J. Food Eng., Vol.176, pp. 128-136, 2016.
  8. [8] A. Samdantsoodol, S. Cang, H. Yu, A. Eardley, and A. Buyantsogt, “Predicting the relationships between virtual enterprises and agility in supply chains,” Expert Syst. Appl., Vol.84, pp. 58-73, 2017.
  9. [9] C. N. Verdouw, A. J. M. Beulens, H. A. Reijers, and J. G. A. J. van der Vorst, “A control model for object virtualization in supply chain management,” Comput. Ind., Vol.68, pp. 116-131, 2015.
  10. [10] M. Matsuda, T. Nishi, M. Hasegawa, and S. Matsumoto, “Virtualization of a supply chain from the manufacturing enterprise view using e-catalogues,” Procedia CIRP, Vol.81, pp. 932-937, 2019.
  11. [11] M. Matsuda and F. Kimura, “Configuration of the digital eco-factory for green production,” Int. J. Automation Technol., Vol.6, No.3, pp. 289-295, 2012.
  12. [12] W. E. Walsh and M. P. Wellman, “Modeling supply chain formation in multiagent systems,” Int. Workshop on Agent-Mediated Electronic Commerce, pp. 94-101, 1999.
  13. [13] Y. Chen, Y. Peng, T. Finin, Y. Labrou, and S. Cost, “Negotiating agents for supply chain management,” Proc. of the AAAI Workshop on Artificial Intelligence for Electronic Commerce, pp. 113-114, 1999.
  14. [14] K. L. Choy and W. B. Lee, “Multi-agent based virtual enterprise supply chain network for order management,” Proc. Portland Int. Conf. on Management of Engineering and Technology (PICMET’01), Vol.1: Book of Summaries (IEEE Cat. No. 01CH37199), Vol.1, pp. 466-467, 2001.
  15. [15] D. A. Ivanov, A. V. Arkhipov, and B. N. Sokolov, “Intelligent supply chain planning in virtual enterprises,” Working Conf. on Virtual Enterprises, pp. 215-223, 2004.
  16. [16] H. J. Ahn and S. J. Park, “Modeling of a multi-agent system for coordination of supply chains with complexity and uncertainty,” Proc. of the 6th Pacific Rim Int. Workshop on Multi-Agents (PRIMA 2003), pp. 13-24, 2003.
  17. [17] K. Tanaka, S.-M. Gu, and J. Zhang, “Designing multi-agent simulation with big time series data for a global supply chain system,” Int. J. Automation Technol., Vol.10, No.4, pp. 632-638, 2016.
  18. [18] F. Lin, Y. Sung, and Y. Lo, “Effects of trust mechanisms on supply-chain performance: A multi-agent simulation study,” Int. J. Electron. Commer., Vol.9, No.4, pp. 91-112, 2005.
  19. [19] M. Wang, J. Liu, H. Wang, W. K. Cheung, and X. Xie, “On-demand e-supply chain integration: A multi-agent constraint-based approach,” Expert Syst. Appl., Vol.34, No.4, pp. 2683-2692, 2008.
  20. [20] Y. Wang and D. Wang, “Multi-agent based intelligent supply chain management,” Proc. of the 9th Int. Conf. on Management Science and Engineering Management, pp. 305-312, 2015.
  21. [21] J. Li, Z. Sheng, and H. Liu, “Multi-agent simulation for the dominant players’ behavior in supply chains,” Simul. Model. Pract. Theory, Vol.18, No.6, pp. 850-859, 2010.
  22. [22] Q. Long, “An agent-based distributed computational experiment framework for virtual supply chain network development,” Expert Syst. Appl., Vol.41, No.9, pp. 4094-4112, 2014.
  23. [23] J. R. Stock, “A research view of supply chain management: Developments and topics for exploration,” ORiON, Vol.25, No.2, pp. 147-160, 2009.
  24. [24] N. Bajgoric, “Always-on enterprise information systems for business continuance: technologies for reliable and scalable operations,” Business Science Reference, 2009.
  25. [25] https://ccl.northwestern.edu/netlogo [Accessed March 8, 2020]

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