A Product Life-Cycle Oriented Approach for Knowledge-Based Product Configuration Systems

Conference paper


Faced with increasing complexity in the global economy, a timely and accurate operation of the market demands an accelerated harmonization of customer and manufacturer perspective in the quotation phase through product configuration systems. An approach for knowledge-based product configuration through the integration of experience and knowledge from the product use phase is presented below. The goal of this approach is to enable a faster and software-controlled harmonization of the different customer’s and the manufacturer’s points of view during the pre-contract phase. Therefore a case-based reasoning method was developed to be integrated in a rule-based product configuration system. It allows a faster ascertainment of customer needs and thereby provides accurate and complete configuration of the provided products.


Product life cycle Product Configuration Requirements Engineering Case-Based Reasoning 



This work has been supported by the integrated research project DIALOG in the topic “Management and Virtualization of Product Development” funded by the German government (BMBF).


  1. 1.
    Jiao, J., Tseng, M. (1999) An information modeling framework for product families to support mass customization manufacturing. Annals of the CIRP, Manufacturing Technology, 48(1):93–98.CrossRefGoogle Scholar
  2. 2.
    Jinsong, Z., Qifu, W., Li, W., Yifang, Z. (2005) Configuration-oriented product modeling and knowledge management for made-to-order manufacturing enterprises. International Journal of Advanced Technology, 25:41–52.CrossRefGoogle Scholar
  3. 3.
    Seliger, G., Gegusch, R., Bilgen, E. (2007) Wissensgenerierung in hybriden Leistungsbündeln. wt Wekstattstechnik online, 97(7/8):522–525.Google Scholar
  4. 4.
    Aurich, J.C., Wolf, N., Mannweiler, C., Siener, M., Schweitzer, E. (2008) Lebenszyklusorientiere Konfiguration investiver PSS. wt Wekstattstechnik online, 98(7/8):593–600.Google Scholar
  5. 5.
    Edler, A. (2001) Nutzung von Felddaten in der qualitätsgetriebenen Produktentwicklung und im Service. Berlin.Google Scholar
  6. 6.
    Ovtcharova, J., Krahtov, K., Rogalski, S. (2007) eHomeostasis methodology in the automotive industry. Proccedings in World Conference on Mass Customization & Personalization (MCP), Boston, MA.Google Scholar
  7. 7.
    Schulte, S. (2006) Integration von Kundenfeedback in die Produktentwicklung zur Optimierung der Kundenzufriedenheit. Bochum.Google Scholar
  8. 8.
    Abramovici, M., Fathi, M., Holland, A., Neubach, M. (2008) PLM-basiertes Integrationskonzept für die Rückführung von Produktnutzungsinformationen in die Produktentwicklung. wt Werkstatttechnik online, 98(7/8):561–567.Google Scholar
  9. 9.
    van Elst, L., Abecker, A. (2004) Ontologies for knowledge management. In: Staab, S., Studer, R. (eds.) Handbook on Ontologies. Springer, Heidelberg, pp. 713–734.Google Scholar
  10. 10.
    Goknil, A., Kurtev, I., van den Berg, K. (2008) A metamodeling approach for reasoning about requirements. Proccedings in ECMDA-FA, LNCS, 5095:310–325.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.FZI Research Center for Information TechnologyKarlsruheGermany

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