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.
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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.
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Kacalak, W., Majewski, M., Budniak, Z. (2015). Intelligent Automated Design of Machine Components Using Antipatterns. In: Jackowski, K., Burduk, R., Walkowiak, K., Wozniak, M., Yin, H. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2015. IDEAL 2015. Lecture Notes in Computer Science(), vol 9375. Springer, Cham. https://doi.org/10.1007/978-3-319-24834-9_30
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DOI: https://doi.org/10.1007/978-3-319-24834-9_30
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