The Taguchi Method as a Means to Verify the Satisfaction of the Information Axiom in Axiomatic Design

  • Sergio RizzutiEmail author
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 34)


The paper deals with the crucial phase of identification of the problems that occur during the design process of industrial products. Designers need to identify the nature and the importance of the problems. An interesting approach to this purpose is the Axiomatic Design, which is the basis for the further application of Robust Design techniques. Among the latter the Taguchi method can be integrated with Axiomatic Design in order to discern the best values of the design parameters and also those values least affected by noises. The study of the interaction of the parameters can reveal the presence of problems, when decoupled matrices are analyzed. The discussion will be made considering the different scenarios of uncoupled and decoupled design matrices and the different reasoning the designer must use. All the information collected can then guide the designers to pursue the design of the best products.


Axiomatic design Robust design Design matrix Information axiom Taguchi method 



The research was supported by a grant of the University of Calabria. The author would like to thank Antonio Rotella and Saverio Parrilla, both MD in Mechanical Engineering, for CAE simulation and data collection related to the design of a device during the course of Product Design and Development at UNICAL.


  1. 1.
    Suh, N.P.: Axiomatic Design: Advances and Applications. Oxford University Press, Oxford (2001)Google Scholar
  2. 2.
    Hong, E.-P., Park, G-J.: Modular design method using the independence axiom and design structure matrix in the conceptual and detailed design stage. In: Proceedings of 6th International Conference on Axiomatic Design (ICAD11), pp. 134-141. Daejeon (2011)Google Scholar
  3. 3.
    Cheng X.: Independent Axiom-Based Robust Design for Nonlinear System. Sensors and Transducers, vol. 16(144–151) (2012)Google Scholar
  4. 4.
    Taguchi G.: Taguchi on Robust Technology Development. ASME Press, New York (1993)Google Scholar
  5. 5.
    Phadke, M.S.: Quality Engineering Using Robust Design. Prentice-Hall, Englewood Cliffs (1989)Google Scholar
  6. 6.
    Frey, D.D., Jahangir, E., Engelhardt, F.: Computing the information content of decoupled designs. Res. Eng. Des. 12, 90–102 (2000)CrossRefGoogle Scholar
  7. 7.
    Park, G.J., Lee, T.H., Lee, K.H., Huang, K.H.: Robust design: an overview. AIAA J. 44(1), 181–191 (2006)CrossRefGoogle Scholar
  8. 8.
    Andersson, P.: On robust design in the conceptual design phase: a qualitative approach. J. Eng. Des. 8(1), 75–89 (1997)CrossRefGoogle Scholar
  9. 9.
    Gijo, E.V., Scaria, J.: Product design by application of Taguchi’s robust engineering using computer simulation. Int. J. Comput. Integr. Manuf. 25(8), 761–773 (2012)Google Scholar
  10. 10.
    Hu, Y., Rao, S.S.: Robust design of horizontal axis wind turbines using Taguchi method. J. Mech. Des. 133, 1–15 (2011)Google Scholar
  11. 11.
    Box, G.E.P., Hunter, J.S., Hunter, W.G.: Statistics for Experimenters. Design, Innovation and Discovery, 2nd edn. Wiley, London (2005)Google Scholar
  12. 12.
    Montgomery, D.C.: Design and Analysis of Experiments, 3rd edn. Wiley, London (1991)Google Scholar
  13. 13.
    Bras, B., Mistree, F.: A compromise decision support problem for axiomatic and robust design. J. Mech. Des. 117, 10–19 (1995)Google Scholar
  14. 14.
    Gu, P., Lu, S., Spiewak, S.: A new approach for robust design of mechanical systems. Ann. CIRP 53(1), 129–133 (2004)CrossRefGoogle Scholar
  15. 15.
    Xiao, R.B., Cheng, X.F.: An analytic approach to the relationship of axiomatic design and robust design. Int. J. Mater. Prod. Technol. 31(2–4), 241–258 (2008)Google Scholar
  16. 16.
    Lijuan, S., Jun, Y., Yu, Z.: An integration design optimization framework of robust design, axiomatic design and reliability-based design. Qual. Reliab. Eng. Int. 27, 959–968 (2011)CrossRefGoogle Scholar
  17. 17.
    Kar, A.K.: Linking axiomatic design and Taguchi methods via information content in design. In: Proceedings of 1st International Conference on Axiomatic Design (ICAD 2000), Cambridge, MA, pp. 219–224 (2000)Google Scholar
  18. 18.
    Hu, M., Yang, K., Taguchi, S.: Enhancing robust design with the aid of TRIZ and axiomatic design. TRIZ J. Part I (October 2000), Part II (November 2000) (2000)Google Scholar
  19. 19.
    Rizzuti, S.: Learn to Design by Mapping Information Among Design Methods. ASME IDETC/CIE, Chicago (IL), USA, 12–15 Aug 2012, DETC2012-70834 (2012)Google Scholar

Copyright information

© Springer India 2015

Authors and Affiliations

  1. 1.Department of Mechanical, Energy and Management EngineeringUniversity of CalabriaRendeItaly

Personalised recommendations