Development of Surface Roughness Prediction by Utilizing Dynamic Cutting Force Ratio

Abstract

This paper presents the development of the in-process surface roughness prediction in the CNC turning process of the plain carbon steel with the coated carbide tool by utilizing the dynamic cutting force ratio. The dynamic cutting forces are measured to analyze the relation between the surface roughness and the cutting conditions. The proposed surface roughness model is developed based on the experimentally obtained results by employing the exponential function with six factors of the cutting speed, the feed rate, the tool nose radius, the depth of cut, the rake angle, and the dynamic cutting force ratio. The dynamic cutting force ratio can be calculated and obtained by taking the ratio of the corresponding time records of the area of the dynamic feed force to that of the dynamic main force. The relation between the dynamic cutting force ratio and the surface roughness can be proved by the obtained frequency of them in frequency domain which are the same frequency. The proposed model has been proved by the new cutting tests with the high accuracy of 91.04% by utilizing the dynamic cutting force ratio.

Monitoring of chip breaking and surface roughness in computer numerical control turning by utilizing wavelet transform of dynamic cutting forces

“…The prediction accuracy of the R a is about 93.67% and the R z is about 93.22%, which are higher than the ones from the previous researches of author. [1][2][3] The values of the in-process predicted surface roughness fall in the 610% measured surface roughness and less than the limited R a of 10 mm and R z of 25 mm. It indicates that the proposed models can be used to predict and control the in-process surface roughness referring to the 610% lines of the specific surface roughness and the limited R a and R z , although the cutting conditions are changed.…”

“…This article presents a development of the previous researches by Tangjitsitcharoen and colleagues 1–3 utilizing the wavelet transform to decompose the dynamic cutting forces in order to classify the surface roughness signal from the chip breaking signals since it is difficult to predict and control the in-process surface roughness while the broken chips occur. However, the relations among the cutting force, the broken chip, and the surface roughness had not been studied.…”

“…4,5 According to the previous researches, an in-process surface roughness prediction had been developed using the cutting force ratio and the experimentally obtained results showed that the ratio of dynamic cutting forces is more effective and accurate than the use of the static cutting force ratio. 2,3 The dynamic cutting forces are hence adopted to monitor the surface roughness. The dynamometer is able to generate the dynamic cutting forces corresponding to the continuous chip, the broken chip, and the surface roughness.…”

In-Process Prediction of Straightness in CNC Turning by Using Wavelet Transform

“…However, the cutting forces cannot be used well to predict the straightness and roundness when the noise signals appear. The relation between the surface roughness and the cutting force had been investigated by using the different cutting tools and the cutting parameters [3].…”

Monitoring of Surface Roughness in Aluminium Turning Process

“…The surface roughness models have been proposed by many researchers [4][5][6][7]. Tangjitsitcharoen [7] developed the in-process surface roughness model that uses the cutting force ratio by employing the exponential function.…”