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Research Paper | Mechanical Engineering | Volume 3 Issue 5, May 2014 | Pages: 1248 - 1252 | India
Use of Artificial Neural Networks to Investigate the Surface Roughness in CNC Milling Machine
Abstract: In order to sustain in the global market competitiveness; maintaining the quality of the component plays a key role to satisfy the customer requirements. Quality can be determined by its surface roughness or by its surface finish. In this work; optimization of machine tool parameters is carried out for CNC milling machine. Machine tools can be used effectively by considering the optimal cutting parameters like speed; feed; and depth of cut. However these parameters greatly influence on the material removal rate and surface finish. This paper aims to investigate the surface roughness values at various speeds; feed and depth of cut conditions by using Artificial Neural Networks. ANN results show that there is no significant difference between the experimental values and predicted roughness values. From these results; conclude that the ANN is best suitable and accurate for solving the cutting parameter optimization.
Keywords: CNC Milling process, Optimization, Surface roughness, Artificial Neural Networks ANN
How to Cite?: M. Vijay Kumar Reddy, "Use of Artificial Neural Networks to Investigate the Surface Roughness in CNC Milling Machine", Volume 3 Issue 5, May 2014, International Journal of Science and Research (IJSR), Pages: 1248-1252, https://www.ijsr.net/getabstract.php?paperid=20132063, DOI: https://dx.doi.org/10.21275/20132063