The Use of Expert Systems Associated to Agents for Routing Suggestions for Service Orders

  • Izabel C. Zattar
  • João Carlos E. Ferreira
Conference paper
Part of the Advanced Concurrent Engineering book series (ACENG)


In dynamic environments, a great obstacle for the integration between process planning and production scheduling is the lack of flexibility for the analysis of alternative resources during the allocation of the jobs on the shop floor. In this phase the process plan is treated as fixed, that is, scheduling does not consider all the possible manufacturing combinations. In order to solve this problem, it was proposed and developed a multiagent system that enables the use of process plans with on-line alternatives. After implementing the system, a large number of tests were carried out, resulting in a database with more than 12,000 simulations. By analyzing the results, it was observed that despite shorter makespan and flow times were attained, the standard deviation was high when comparing with other approaches found in the literature. As the problem is significantly complex, involving many parts, resources and alternative plans, an Expert Agent based on the Java Expert System Shell (JESS) language was implemented which, through the application of rules, filters the information in the database of simulations and provides the system with an adequate suggestion of the route to be executed.


Multiagent systems Expert systems Routing 


  1. 1.
    Aytug H, Bhattachary S, Koehler GJ, Snowdon J. A review of machine learning in scheduling. IEEE Trans Eng Manage. 1994;41(22):165–71.CrossRefGoogle Scholar
  2. 2.
    Cruces ALL, Arriaga FD. Reactive agent design for intelligent tutoring systems. Cyber Syst Int J. 2000;31:1–47.zbMATHCrossRefGoogle Scholar
  3. 3.
    Shen W, Wang L, Hao Q. Agent-based distributed manufacturing process planning and scheduling: a state-of-art survey. IEEE transactions on systems, man and cybernetics—part C: applications and reviews 2006;36:563–571.Google Scholar
  4. 4.
    Aldea A, Banares A, Jimenez R, Moreno L, Martinez J, Riano D. The scope of application of multi-agent systems in the process industry: three case studies. Exp Syst Appl. 2004;26:39–47.CrossRefGoogle Scholar
  5. 5.
    Gjerdrum J, Shah N, Papageorgiou LG. A combined optimization and agent-based approach to supply chain modeling and performance assessment. Prod Plann Control. 2001;12:81–8.CrossRefGoogle Scholar
  6. 6.
    Rezende SO. (Org). Sistemas Inteligentes: Fundamentos E Aplicações. Barueri: Manole, 2005. p. 525.Google Scholar
  7. 7.
    Zattar IC, Ferrreira JCE, Rodrigues JGGG, Sousa CHB. Integration between process planning and scheduling using feature-based time-extended negotiation protocols in a multi-agent system. 2008; p. 71-89.Google Scholar
  8. 8.
    Foundation for Intelligent Physical Agents (FIPA) Available at: Accessed 13 Mar 2007.
  9. 9.
    Jade Administrator’s Guide, 2005. Available in Accessed 01th Jun 2007.
  10. 10.
    Eclipse—an open development platform. Available in Accessed 03 Jan 2008.
  11. 11.
    MySQL. Available in Accessed 05 Dec 2007.
  12. 12.
    JESS, the Rule Engine for the JAVA. Available in Accessed 13 Dec 2007.
  13. 13.
    Friedman-Hill E. JESS in action: rule-based systems In JAVA. Ct, USA: Manning Publications; 2003.Google Scholar
  14. 14.
    Cardoso HL. Integrating Jade and JESS. Available in: http://Jade.Tilab.Com/Doc/Tutorials/Jade-JESS/Jade_JESS.Html. Accessed 18 Dec 2007.
  15. 15.
    Zattar IC. Modelo de simulação baseado agentes para o estudo da influência de planos de processos alternativos na programação da produção em sistemas de manufatura com layout funcional. Doctor Degree thesis, Universidade Federal de Santa Catarina; 2010.Google Scholar
  16. 16.
    Kim YK, Park K, Ko J. A symbiotic evolutionary algorithm for the integration of process planning and job shop scheduling. Comput Oper Res. 2003;30:1151–71.MathSciNetzbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Limited 2010

Authors and Affiliations

  1. 1.Universidade Federal do Paraná, Setor de TecnologiaCuritibaBrazil
  2. 2.Universidade Federal de Santa CatarinaSanta CatarinaBrazil

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