Advanced Prediction of Surface Roughness by Monitoring of Dynamic Cutting Forces in CNC Turning Process

Author:

Tangjitsitcharoen Somkiat1

Affiliation:

1. Chulalongkorn University

Abstract

The aim of this research is to investigate the relation between the surface roughness and the dynamic cutting force ratio during the in-process cutting in CNC turning process. The proposed surface roughness model is developed based on the experimentally obtained results by employing the exponential function with five factors of the cutting speed, the feed rate, the tool nose radius, the depth of cut, and the dynamic cutting force ratio. The dynamic cutting force ratio is proposed to predict the surface roughness during the cutting, which can be calculated and obtained by taking the ratio of the corresponding time records of the area of thedynamic feed force to that of the dynamic main force. The in-process relation between dynamic cutting force ratio and surface roughness can be proved by the frequency of the dynamic cutting force which corresponds to the surface roughnessfrequency. The multiple regression analysis is utilized to calculate the regression coefficients with the use of the least square method at 95% confident level. The proposed model has been verified by the new cutting tests. It is understood that the developed surface roughness model can be used to predict the in-process surface roughness with the high accuracy of 90.3% by utilizing the dynamic cutting force ratio.

Publisher

Trans Tech Publications, Ltd.

Reference11 articles.

1. S. Tangjitsitcharoen. (2010). NAMRI/SME 38: 307-315.

2. S. Tangjitsitcharoen. (2011). Advance Materials Research 199-200. 1958-(1966).

3. Y. Mishing, in: Diffusion Processes in Advanced Technological Materials, edtied by D. Gupta Noyes Publications/William Andrew Publising, Norwich, NY (2004), in press.

4. D.I. Lalwani, N.K. Mehta and P.K. Jain: J Mater Process Technol. Vol. 206 (2008), p.167.

5. M.G. Ignatov, A.E. Perminov and E. Yu Prokof'ev: Russian Engineering Reserch. Vol. 28-9 (2008), p.864.

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1. Comparison of Neural Networks and Regression Analysis to Predict In-process Straightness in CNC Turning;Procedia Manufacturing;2020

2. In-process prediction of roundness based on dynamic cutting forces;The International Journal of Advanced Manufacturing Technology;2017-09-06

3. Monitoring of chip breaking and surface roughness in computer numerical control turning by utilizing wavelet transform of dynamic cutting forces;Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture;2015-12-16

4. A wavelet approach to predict surface roughness in ball-end milling;Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture;2015-10-29

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