Abstract
The objective of this study is to examine the influence of machining parameters on surface finish in turning of medical steel. A new approach in modeling surface roughness which uses design of experiments is described in this paper. The values of surface roughness predicted by different models are then compared. Used were adaptive-neuro-fuzzy-inference system (ANFIS). The results showed that the proposed system can significantly increase the accuracy of the product profile when compared to the conventional approaches. The results indicate that the design of experiments with central composition plan modeling technique can be effectively used for the prediction of the surface roughness for medical steel difficult to machining. Optimizations of surface roughness parameters was done by use of ant colony method.
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The paper is the result of the research within the project TR 35015 financed by the ministry of science and technological development of the Republic of Serbia and CEEPUS project.
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Kovač, P. et al. (2020). Modelling and Optimization of Surface Roughness Parameters of Stainless Steel by Artificial Intelligence Methods. In: Durakbasa, N., Gençyılmaz, M. (eds) Proceedings of the International Symposium for Production Research 2019. ISPR ISPR 2019 2019. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-31343-2_1
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