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

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.

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

“…It is proved that the in-process surface roughness can be predicted well in CNC turning process by using the ratio of dynamic cutting forces [7]. The force sensor is employed to detect the chatter in the grinding process [8] and the milling process [9].…”

Monitoring of Surface Roughness in Aluminium Turning Process

“…It means that the cutting forces are lower and easy to cut, which results in a good quality of surface finish [7,10,11]. The large depth of cut brings about the larger cutting area and the higher dynamic cutting force which affects the vibration of cutting tool and workpiece during the cutting.…”