Surface roughness modeling of CBN hard steel turning
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Дата
2018
ORCID
DOI
Науковий ступінь
Рівень дисертації
Шифр та назва спеціальності
Рада захисту
Установа захисту
Науковий керівник
Члени комітету
Видавець
Национальный технический университет "Харьковский политехнический институт"
Анотація
Study in the paper investigate the influence of the cutting conditions parameters on surface roughness parameters during turning of hard steel with cubic boron nitrite cutting tool insert. For the modeling of surface roughness parameters was used central compositional design of experiment and artificial neural network as well. The values of surface roughness parameters Average mean arithmetic surface roughness (Ra) and Maximal surface roughness (Rmax) were predicted by this two-modeling methodology and determined models were then compared. The results showed that the proposed systems can significantly increase the accuracy of the product profile when compared to the conventional approaches. The results indicate that the design of experiments modeling technique and artificial neural network can be effectively used for the prediction of the surface roughness parameters of hard steel and determined significantly influential cutting conditions parameters.
Опис
Ключові слова
RSM, neural network, hard steel, input factor, gradient descent method
Бібліографічний опис
Surface roughness modeling of CBN hard steel turning / P. Kovač [et al.] // Резание и инструменты в технологических системах = Cutting & tools in technological systems : междунар. науч.-техн. сб. – Харьков : НТУ "ХПИ", 2018. – Вып. 89. – С. 78-87.