Advertisement

Product Modeling on Multiple Abstraction Levels

  • Kaj A. Jørgensen
Chapter
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 87)

Abstract

Typically, Mass Customization (MC) is most often described in relationship with mass production companies. However, in more and more cases, it is shown what MC means for manufacturing-to-order companies and even for engineer-to-order companies. This paper is initiated by some of the challenges associated with modeling of products and product families in such companies. For some of them, the situation is made extreme by market conditions, which imply long order horizons and many changes of the orders both before and after order acceptance.

With focus on these challenges, an approach is described about modeling of product families on multiple abstraction levels in a way where customer driven product configuration is concentrated on decisions, which are relatively invariant throughout order processing. The approach, which is used here, is based on the theory of general systems and outlined in combination with the abstraction mechanisms classification and composition together with object-oriented analysis and design. A generic model component is presented for enabling representation of models as data models.

Extending a model with more and more details is very typically and is the traditional view derived from the predominant type of modeling tools, e.g. CAD software, where the primary focus is on geometry. It is, however, very important to state that modeling must also be performed on different levels of abstraction. First, the abstraction levels must be identified and, subsequently, each abstraction level must be specified in greater detail.

The modeling approach includes guidelines about how the individual levels can be identified and defined. It is argued that the abstraction levels can be utilized in connection with both analytic and synthetic modeling. Hence, they can be applied to both requirement definition and design by modeling. By this approach, it is also shown how the focus of product configuration must be shifted to identification and definition of attributes instead of modules and components and considerations about the ability to perform the functions, which are required by the customer, are very primary and should be addressed at higher abstraction levels.

Key words

Mass customization product configuration product model product family model abstraction level information modeling classification composition object-oriented analysis and design module types 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Andreasen, M. M. (2003): Relations between modularisation and product structuring. In Proceedings of the 6th workshop on Product Structuring — application of product models, MEK-DTU, Denmark, pp. 1–15.Google Scholar
  2. Berman, B. (2002): Should your firm adopt a mass customization strategy? Business Horizons, 45(4):51–60.CrossRefGoogle Scholar
  3. Da Silveira, G. / Borenstein, D. / Fogliatto, F. S. (2001): Mass customization: Literature review and research directions. Int. Journal of Production Economics, 72:1–13.CrossRefGoogle Scholar
  4. Davis, S. (1989): From future perfect: Mass customizing. Planning Review.Google Scholar
  5. Du, X. / Jiao, J. / Tseng, M. M. (2000): Architecture of product family for mass customization. In Proceedings of the 2000 IEEE International Conference on Management of Innovation and Technology.Google Scholar
  6. Felfernig, A. / Friedrich, G. / Jannach, D. (2001): Conceptual modeling for configuration of mass-customizable products. Artificial Intelligence in Engineering, 15:165–176.CrossRefGoogle Scholar
  7. Faltings, B. / Freuder, E. C. (Ed.): Configuration-Getting it right. Special issue of IEEE Intelligent Systems, Vol.13, No. 4, July/August 1998.Google Scholar
  8. Gilmore, J. / Pine, J. (1997): The four faces of mass customization. Harvard Business Review 75(1).Google Scholar
  9. Hammer, M. / McLeod, D. (1978): The Semantic Data Model: A Modelling Mechanism for Data Base Applications. Proceedings of ACM/SIGMOD International Conference on Management of Data. Austin Texas, pp. 144–156, 1978.Google Scholar
  10. Hvam, L. (1994): Anvendelse af produktmodellering,-set ud fra en arbejdsforberedelsessynsvinkel. PhD thesis, Driftteknisk Institut, DTU.Google Scholar
  11. Hvam, L. (1999): A procedure for building product models. Robotics and Computer-Integrated Manufacturing, 15:77–87.CrossRefGoogle Scholar
  12. Jazayeri, M. / Ran, A., / van den Linden, F. (2000): Software architecture for product families: Principles and practice. Addison-Wesley, 2000.Google Scholar
  13. Jiao, J. / Tseng, M. M. / Duffy, V. G. / Lin, F. (1998): Product family modeling for mass customization. Computers & Industrial Engineering, 35:495–198.CrossRefGoogle Scholar
  14. Jørgensen, K. A. (1998): Information Modelling: foundation, abstraction mechanisms and approach. In: Journal of Intelligent Manufacturing, Vol.9, No.6, 1998, Kluwer Academic Publishers, The Netherlands.Google Scholar
  15. Jørgensen, K. A. (2002): A Selection of System Concepts. Aalborg University, Department of Production, 2002.Google Scholar
  16. Jørgensen, K. A. (2003): Information Models Representing Product Families. Proceedings of 6th Workshop on Product Structuring, 23rd and 24th January 2003, Technical University of Denmark, Dept. of Mechanical Engineering.Google Scholar
  17. Lampel, J. / Mintzberg, H. (1996): Customizing customization. Sloan Management Review, 38:21–30.Google Scholar
  18. Männistö, T. / Soininen, T. / Sulonen, R. (2001): Product Configuration View to Software Product Families. In: Proceedings of Software Configuration Management Workshop (SCM-10). Toronto, 2001.Google Scholar
  19. Pine, B. J. (1993): Mass Customization-The New Frontier in Business Competition. Harvard Business School Press, Boston Massachusetts, 1993.Google Scholar
  20. Pine, J. / Victor, B. / Boyton, A. (1993): Making mass customization work. Harvard Business Review 71(5), 71(5):108–119.Google Scholar
  21. Reichwald, R. / Piller, F. T. / Möslein, K. (2000): Information as a critical success factor on Why even a customized shoe not always fits. In Proceedings Administrative Sciences Association of Canada, International Federation of Scholarly Associations of Management 2000 Conference.Google Scholar
  22. Rosch, E. (1978): Principles of Categorisation. In: Cognition and Categorization. Laurence Erlbaum, Hillsdale, Jew Jersey, 1978.Google Scholar
  23. Sabin, D. / Weigel, R. (1998): Product Configuration Frameworks-A survey. In IEEE intelligent systems & their applications, 13(4):42–49, 1998.CrossRefGoogle Scholar
  24. Smith, J. M. / Smith, D. C. P. (1977a): Database Abstractions: Aggregation. Communications of the ACM, Vol. 20, No.6, pp. 405–413 New York 1977.CrossRefGoogle Scholar
  25. Smith, J. M. / Smith, D. C. P. (1977b): Database Abstractions: Aggregation and Generalization. ACM transactions on Data Base Systems, vol.2, no.2, pp. 105–133 New York 1977.CrossRefGoogle Scholar
  26. Sowa, J. F. (1984): Conceptual Structures: Information Processing in Mind and Machine. Addison-Wesley, 1984.Google Scholar

Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  • Kaj A. Jørgensen
    • 1
  1. 1.Department of ProductionAalborg UniversityAalborg

Personalised recommendations