Skip to main content
SpringerLink
Log in

Application of the classical levels of intelligence to structuring the control system in an automated distribution centre

  • Published:
Journal of Intelligent Manufacturing Aims and scope Submit manuscript

Abstract

Traditional management and control models can benefit from added levels of intelligence to increase their capability to adapt to the continuous changes in global markets. After reviewing the classical definition of intelligence and its levels, this paper provides a new approach to help increase the responsiveness of management and control to changes and disturbances in the manufacturing supply chain. The ancient concept of the “Tertium Quid” has inspired a three-level community of agents (MAS-TRIO) that is proposed to improve the coordination of all actors involved. The proposed model combines Multi-Agent Systems (MAS) with Radio-Frequency Identification (RFID) to make possible a certain level of Autonomous Intelligence in the decision-taking process. This paper analyses how these levels of intelligence can be applied to management and control, and the performance of the proposed model has been tested at low and mid-levels on an experimental platform representing the facilities of a distribution centre controlled by a network of programmable logic controllers (PLCs).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Brennan, R., Gruver, W., & Hall, K. (2011). Forward-special issue on industrial applications of holonic manufacturing systems. Systems, man, and cybernetics, part C: Applications and reviews, IEEE transactions on, 41(1), 1–3.

    Article  Google Scholar 

  • Bussmann, S., Jennings, N., & Wooldridge, M. J. (2004). Multiagent systems for manufacturing control: A design methodology. New York: Springer.

    Book  Google Scholar 

  • BYG Simulation. (2012). About Grasp 10. http://www.bygsimulation.com/RoboticsAndAutomation/Grasp10.asp. Accessed 9 January 2013.

  • Encinas, J., & de las Morenas, J. (2012). Improvements in operations management applied to a 3D simulation connected to a physical platform. Journal of Intelligent Manufacturing, 23(3), 845–856. doi:10.1007/s10845-010-0441-0.

    Article  Google Scholar 

  • Evertsz, R., Fletcher, M., Jones, R., Jarvis, J., Brusey, J., & Dance, S. (2004). Implementing industrial multi-agent systems using JACK. In Programming Multi-Agent Systems (Vol. 3067, pp. 18–48), Lecture Notes in Computer Science. Heidelberg: Springer Berlin.

  • Finkenzeller, K. (2010). RFID handbook: Fundamentals and applications in contactless smart cards, radio frequency identification and near-field communication. New York: Wiley.

  • García, A., & Cenjor, A. (2007). Sistema Heterárquico de Control Basado en Agentes para Sistemas de Fabricación. Revista iberoamericana de automática e informática industrial (RIAI), 4(1), 83.

    Article  Google Scholar 

  • García Ansola, P., de las Morenas, J., García, A., & Otamendi, J. (2012). Distributed decision support system for airport ground handling management using WSN and MAS. Engineering Applications of Artificial Intelligence, 25(3), 544–553. doi:10.1016/j.engappai.2011.11.005.

    Article  Google Scholar 

  • Gardner, J. E. S. (2006). Exponential smoothing: The state of the art-part II. International Journal of Forecasting, 22(4), 637–666.

    Article  Google Scholar 

  • Garijo, F. J. (2002). Tecnología de agentes: Experiencias y perspectivas para el desarrollo de nuevos servicios y aplicaciones. Boletin tic n\(^{o}\) 24.

  • Khalgui, M., Mosbahi, O., Hanisch, H.-M., & Li, Z. (2012). A multi-agent architectural solution for coherent distributed reconfigurations of function blocks. Journal of Intelligent Manufacturing, 23(6), 2531–2549. doi:10.1007/s10845-011-0556-y.

    Article  Google Scholar 

  • Leitão, P. (2009). Agent-based distributed manufacturing control: A state-of-the-art survey. Engineering Applications of Artificial Intelligence, 22(7), 979–991.

    Article  Google Scholar 

  • Leitão, P., & Restivo, F. (2006). ADACOR: A holonic architecture for agile and adaptive manufacturing control. Computers in Industry, 57(2), 121–130.

    Article  Google Scholar 

  • McFarlane, D. (2012). Product intelligence: Theory and practice. In 14th IFAC symposium on information control problems in manufacturing, Bucharest (Romania), 2012 (Vol. 14). doi:10.3182/20120523-3-RO-2023.00441.

  • McFarlane, D., Sarma, S., Chirn, J. L., Wong, C. Y., & Ashton, K. (2003). Auto ID systems and intelligent manufacturing control. Engineering Applications of Artificial Intelligence, 16(4), 365–376.

    Article  Google Scholar 

  • Mendes, J. M., Leitão, P., Colombo, A. W., & Restivo, F. (2008). Service-oriented control architecture for reconfigurable production systems. In 6th IEEE international conference on industrial informatics, 2008 (pp. 744–749).

  • Meyer, G. G., Främling, K., & Holmström, J. (2009). Intelligent products: A survey. Computers in Industry, 60(3), 137–148.

    Article  Google Scholar 

  • Pannequin, R., & Thomas, A. (2012). Another interpretation of stigmergy for product-driven systems architecture. Journal of Intelligent Manufacturing, 23(6), 2587–2599. doi:10.1007/s10845-011-0588-3.

    Article  Google Scholar 

  • Pechouček, M., & Mařík, V. (2008). Industrial deployment of multi-agent technologies: Review and selected case studies. Autonomous Agents and Multi-Agent Systems, 17(3), 397–431. doi:10.1007/s10458-008-9050-0.

    Article  Google Scholar 

  • Qu, T., Yang, H. D., Huang, G., Zhang, Y. F., Luo, H., & Qin, W. (2012). A case of implementing RFID-based real-time shop-floor material management for household electrical appliance manufacturers. Journal of Intelligent Manufacturing, 23(6), 2343–2356. doi:10.1007/s10845-010-0476-2.

    Article  Google Scholar 

  • Radakovič, M., Obitko, M., & Mařík, V. (2012). Dynamic explicitly specified behaviors in distributed agent-based industrial solutions. Journal of Intelligent Manufacturing, 23(6), 2601–2621. doi:10.1007/s10845-011-0593-6.

    Article  Google Scholar 

  • Rao, A. S., Georgeff, M. P. (1995). BDI agents: From theory to practice. In Proceedings of the first international conference on multi-agent systems (ICMAS-95), 1995 (pp. 312–319).

  • Ren, Z., Yang, F., Bouchlaghem, N. M., & Anumba, C. J. (2011). Multi-disciplinary collaborative building design-A comparative study between multi-agent systems and multi-disciplinary optimisation approaches. Automation in Construction, 20(5), 537–549. doi:10.1016/j.autcon.2010.11.020.

  • Soto, J., Vizcaino, A., Portillo, J., Piattini, M., & Kusche, O. (2009). A two-layer multi-agent architecture to facilitate knowledge sharing within communities of practice. Inteligencia artificial, 13(42).

  • Theiss, S., Vasyutynskyy, V., & Kabitzsch, K. (2009). Software agents in industry: A customized framework in theory and praxis. IEEE Transactions on Industrial Informatics, 5(2), 147–156.

    Article  Google Scholar 

  • Thomas, A., Trentesaux, D., & Valckenaers, P. (2012). Intelligent distributed production control. Journal of Intelligent Manufacturing, 23(6), 2507–2512. doi:10.1007/s10845-011-0601-x.

    Article  Google Scholar 

  • Thorne, A., McFarlane, D., Hodges, S., Smith, S., Harrison, M., & Brusey, J. et al. (2003). The autoID automation laboratory: Building tomorrow’s systems today. Auto-ID centre white papers. University of Cambridge.

  • Valckenaers, P., Germain, B. S., Verstraete, P., Van Belle, J., Hadeli, & Van Brussel, H. (2009). Intelligent products: Agere versus essere. Computers in Industry, 60(3), 217–228.

    Article  Google Scholar 

  • Valckenaers, P., Hadeli, S., Germain, B. S., Verstraete, P., & Van Brussel, H. (2007). MAS coordination and control based on stigmergy. Computers in Industry, 58(7), 621–629.

    Article  Google Scholar 

  • Vrba, P., Tichý, P., Mařík, V., Hall, K. H., Staron, R. J., Maturana, F. P., et al. (2011). Rockwell automation’s holonic and multiagent control systems compendium. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 41(1), 14–30.

    Article  Google Scholar 

  • Wooldridge, M., & Jennings, N. (1995). Intelligent agents: Theory and practice. Knowledge Engineering Review, 10(2), 115–152.

    Article  Google Scholar 

  • Wooldridge, M. J. (2002). An introduction to multiagent systems. New York: Wiley.

Download references

Author information

Authors and Affiliations

  1. School of Industrial Engineering, University of Castilla-La Mancha, Ciudad Real, Spain

    Andrés García Higuera & Javier de las Morenas

Authors
  1. Andrés García Higuera
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Javier de las Morenas
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Javier de las Morenas.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Higuera, A.G., de las Morenas, J. Application of the classical levels of intelligence to structuring the control system in an automated distribution centre. J Intell Manuf 25, 1197–1206 (2014). https://doi.org/10.1007/s10845-013-0739-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10845-013-0739-9

Keywords

Search

Navigation