Advertisement

Intelligent Automated Design of Machine Components Using Antipatterns

  • Wojciech Kacalak
  • Maciej MajewskiEmail author
  • Zbigniew Budniak
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9375)

Abstract

The article presents a methodology for the analysis of similarities between structural features of designed machine elements and the corresponding antipatterns. This methodology allows normalization of selected design solutions’ characteristic features. The defined antipatterns are generic definitions of the possible incorrect design solutions. The article also presents antipatterns’ attributes, as well as classification based on the root causes of errors in designed solutions. Examples of a step shaft have been used to illustrate the methodology of designed solution and its antipattern correspondence evaluation. Root causes of a design error, its importance, and similarities shared with other design errors have been analyzed for each of the presented antipatterns. Correctly designed shafts - not having the characteristics of an antipattern - have also been presented.

Keywords

Intelligent automated design Interactive design system Intelligent interface Antipatterns Design automation Neural networks 

Notes

Acknowledgements

This project was financed from the funds of the National Science Centre (Poland) allocated on the basis of the decision number DEC-2012/05/B/ST8/02802.

References

  1. 1.
    Brown, W.J., McCormick, H.W., Thomas, S.W.: AntiPatterns in Project Management. Wiley, New York (2000) Google Scholar
  2. 2.
    Kacalak, W., Majewski, M.: New Intelligent interactive automated systems for design of machine elements and assemblies. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds.) ICONIP 2012, Part IV. LNCS, vol. 7666, pp. 115–122. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  3. 3.
    Majewski, M., Zurada, J.M.: Sentence recognition using artificial neural networks. Knowl. Based Syst. 21(7), 629–635 (2008). ElsevierCrossRefGoogle Scholar
  4. 4.
    Piegl, L.A.: Ten challenges in computer-aided design. Comput. Aided Des. 37(4), 461–470 (2005). ElsevierCrossRefGoogle Scholar
  5. 5.
    Riel, A.J.: Object-Oriented Design Heuristics. Addison-Wesley, Reading (1996)Google Scholar
  6. 6.
    Specht, D.F.: Probabilistic neural networks. Neural Netw. 3(1), 109–118 (1990)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Wojciech Kacalak
    • 1
  • Maciej Majewski
    • 1
    Email author
  • Zbigniew Budniak
    • 1
  1. 1.Faculty of Mechanical EngineeringKoszalin University of TechnologyKoszalinPoland

Personalised recommendations