In-Process Prediction of Surface Roughness in Grinding Process by Monitoring of Cutting Force Ratio


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The purpose of this research is to develop the models to predict the average surface roughness and the surface roughness during the in-process grinding by monitoring the cutting force ratio. The proposed models are developed based on the experimentally obtained results by employing the exponential function with four factors, which are the spindle speed, the feed rate, the depth of cut, and the cutting force ratio. The experimentally obtained results showed that the dimensionless cutting force ratio is usable to predict the surface roughness during the grinding process, which can be calculated and obtained by taking the ratio of the corresponding time records of the cutting force Fy in the spindle speed direction to that of the cutting force Fz in the radial wheel direction. The multiple regression analysis is utilized to calculate the regression coefficients with the use of the least square method at 95% confident level. The experimentally obtained models have been verified by the new cutting tests. It is proved that the developed surface roughness models can be used to predict the in-process surface roughness with the high accuracy of 93.9% for the average surface roughness and 92.8% for the surface roughness.



Edited by:

Bale V. Reddy, Shishir Kumar Sahu, A. Kandasamy and Manuel de La Sen




V. Thammasing and S. Tangjitsitcharoen, "In-Process Prediction of Surface Roughness in Grinding Process by Monitoring of Cutting Force Ratio", Applied Mechanics and Materials, Vol. 627, pp. 29-34, 2014

Online since:

September 2014




* - Corresponding Author

[1] H. Kaliszer: Adaptive control in grinding process, Proceeding of the 4th International conference on Production Engineering, Tokyo (1980), pp.679-593.

[2] M.A. Kamely, S.M. Kamil and C.W. Chong: Mathematical Modeling of Surface Roughness in Surface Grinding Operation, International Journal of Engineering and Natural Sciences Vol. 5 (2011), pp.146-149.

[3] Y.D. Gong, B. Wang, W.S. Wang: The simulation of grinding wheels and ground surface roughness based on virtual reality technology, Journal of Materials Processing technology, Vol. 129 (2002), pp.123-126.

[4] H. Demir, A. Gullu, I. Ciftci, U. Seker: An Investigation into the Influences of Grain Size and Grinding Parameters on Surface Roughness and Grinding Forces when Grinding, Journal of Mechanical Engineering, Vol. 56 (2010), pp.447-454.

[5] H. Baseri: Workpiece Surface Roughness Prediction in Grinding Process for Different Disc Dressing Conditions, International Conference on Mechanical and Electrical Technology (2010), pp.209-212.

[6] M. Sedlaček, B. Podgornik, J. Vižintin: Influence of surface preparation on roughness parameters, friction and wear, Wear, Vol. 266 (2009), pp.482-487.


[7] M. Hasegawa, M. Saito, M. Mitsuhashi, S. Kawamura: Statistically designed model of ground surface roughness, Proceeding of the 4th International conference on Production Engineering, Tokyo (1980), pp.600-605.

[8] N. Zouaghi, Y. Ichida, N. B. Frej: Grinding Mode Identification of Silicon Carbide by Using neural network, Proceeding of the 3th International conference on Progress of cutting and grinding, Osaka, Japan, Vol. 3 (1996), pp.342-347.

[9] S. Tangjitsitcharoen: In-process monitoring and prediction of surface roughness in CNC Turning process, Advanced Materials Research, Vol. 199-200 (2011), p.1928-(1966).


[10] S. Tangjitsitcharoen: In-process Prediction of Surface Roughness by Utilizing the Cutting Force Ratio, NAMRI/SME, Vol. 38 (2010), pp.307-315.