Web-Based Decision Support System for Orders Planning

  • António Arrais-Castro
  • Maria Leonilde R. Varela
  • Sílvio Carmo-Silva
Conference paper
Part of the Intelligent Systems, Control and Automation: Science and Engineering book series (ISCA, volume 61)


Competition in the global economy is intensifying the implementation of the mass customization paradigm. This requires a substantial increase in the personalized interaction between client and producer. Agility in the order-production-delivery cycle optimization is a key element for industrial enterprises as a means to meet requirements of this paradigm. The use of agile methodologies for this purpose requires improving processes of product specification and product data management. Under today’s technology this tends to be predominantly carried out with the aid of the Internet using mostly web services. For a company, this also requires better integration of front-office processes (interaction with the outside) and back office (including production processes). Mass Customization scenarios are characterized by large product variety dependent on product specific requirements of individual customers. In this process there is a need to provide the customer with tools for easy product specification, selection or configuration. Web-based configurators can provide an opportunity to both producer and customer, through an interactive process, for a more formal, faster, effective and better product and orders specification. In this paper, we propose an architecture and describe functionalities of a web-based system for interactive products and customer orders configuration. The proposed system can also be a valuable tool to support production and delivery.


Mass configuration Web services Product configurator 



This work was developed under the scope of project PEst-OE/EME/UI0252/2011, financed by The Foundation for Science and Technology – FCT.


  1. 1.
    Pine J, Gilmore J (1999) The experience economy. Harvard Business School Press, BostonGoogle Scholar
  2. 2.
    Piller F (2002) Customer interaction and digitizability – a structural approach to mass customization. In: Rautenstrauch C (ed) Moving towards mass customization. Springer, Heidelberg/Berlin/New York, pp 119–138CrossRefGoogle Scholar
  3. 3.
    Davis SM (1987) Future perfect. Addison-Wesley, New YorkGoogle Scholar
  4. 4.
    Tseng M, Jiao J (2001) Mass customization. In: Gavriel Salvendy (ed) Handbook of industrial engineering, technology and operation management, 3rd edn. New YorkGoogle Scholar
  5. 5.
    Blattberg RC, Glazer R (1994) In: Blattberg RC (ed) Marketing in the information revolution, the marketing information revolution. Harvard Business School Press, Boston, pp 9–29Google Scholar
  6. 6.
    Goddard WE (1986) Just-in-time: surviving by breaking tradition. Oliver Wight Ltd. Pub, USAGoogle Scholar
  7. 7.
    Kidd PT (1994) Agile manufacturing forging new frontiers. Addison-Wesley, ReadingGoogle Scholar
  8. 8.
    Nagel R, Dove R (1991) Twenty-first century manufacturing enterprise strategy – an industry led review, vol 1 and 2. Iacocca Institute, Leigh University, BethlehemGoogle Scholar
  9. 9.
    Hiramatsu A, Naito A, Ikkai Y, Ohkawa T, Komoda N (1997) Case based function tree generator for client–server systems configuration design. In: Proceedings of the IEEE international conference on systems, man and cybernetics, Orlando, FL, USAGoogle Scholar
  10. 10.
    Hong G, Hu L, Xue D, Tu Y, Xiong Y (2008) Identification of the optimal product configuration and parameters based on individual customer requirements on performance and costs in one-of-a-kind production. Int J Prod Res, Taylor & Francis, Ablingdon, ROYAUME-UNI, 46(12):3297–3326MATHCrossRefGoogle Scholar
  11. 11.
    Jiao J, Helander MG (2006) Development of an electronic configure-to-order platform for customized product development. Comput Ind 57(3 (Abr)):231–244CrossRefGoogle Scholar
  12. 12.
    Lee HJ, Lee JK (2005) An effective customization procedure with configurable standard models. Decis Support Syst 41(1):262–278CrossRefGoogle Scholar
  13. 13.
    Li B, Chen L, Huang Z, Zhong Y (2006) Product configuration optimization using a multiobjective genetic algorithm. Int J Adv Manuf Technol 30(1–2):20–29CrossRefGoogle Scholar
  14. 14.
    Luo X, Tu Y, Tang J, Kwong C (2008) Optimizing customer’s selection for configurable product in B2C e-commerce application. Comput Ind 59(8 (Out)):767–776CrossRefGoogle Scholar
  15. 15.
    Mailharro D (1998) A classification and constraint-based framework for configuration. Artif Intell Eng Des Anal Manuf 12(4):383–395Google Scholar
  16. 16.
    McGuinness D, Wright J (1998) An industrial-strength description logic-based configurator platform. IEEE Intell Syst 13(4):69–77CrossRefGoogle Scholar
  17. 17.
    Mittal S, Frayman F (1989) Towards a generic model of configuration tasks. In: Proceedings of the 11th international joint conference on artificial intelligence. IJCAI '89. San Mateo, CA, Morgan Kaufmann, pp 1395–1401Google Scholar
  18. 18.
    Sabin D, Weigel R (1998) Product configuration frameworks – a survey. IEEE Intell Syst 13(4):42–49CrossRefGoogle Scholar
  19. 19.
    Tseng H, Chang C, Chang S (2005) Applying case-based reasoning for product configuration in mass customization environments. Expert Syst Appl 29:913–925CrossRefGoogle Scholar
  20. 20.
    Yang D, Dong M, Miao E (2008) Development of a product configuration system with an ontology-based approach. Comput Aided Des 40(8 (Ago)):863–878CrossRefGoogle Scholar
  21. 21.
    Yeh J, Wu T, Chang J (2007) Parallel genetic algorithms for product configuration management on PC cluster systems. Int J Adv Manuf Technol 31(11–12)Google Scholar
  22. 22.
    Zhou C, Lin Z, Liu C (2008) Customer-driven product configuration optimization for assemble-to-order manufacturing enterprises. Int J Adv Manuf Technol, Springer, 38(1–2):185–194CrossRefGoogle Scholar
  23. 23.
    Castro AA, Varela MLR, Carmo-Silva S (2009) Products and orders configurator based on web services. In: Proceedings of the iDEMi09 – international conference on integration of design, engineering and management for innovation, Porto, PortugalGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • António Arrais-Castro
    • 1
  • Maria Leonilde R. Varela
    • 1
  • Sílvio Carmo-Silva
    • 1
  1. 1.Department of Production and Systems, School of EngineeringUniversity of MinhoGuimarãesPortugal

Personalised recommendations