Correlation analysis of the roughness as function of cutting speed and feed rate (the roughness as function of machining parameters)

Abstract

Experimental evaluations based on statistical and scientific criteria play fundamental role in identification of optimal performance parameters in manufacturing engineering. Based on this premise, the Doehlert's experimental planning method was applied to external cylindrical turning process of ABNT 1045 steel, with the purpose of determining the roughness correlation as a function of the cutting speed (Vc) and feed rate (f). The Doehlert's matrix was defined with five levels for feed rate and three levels for cutting speed, according to coded variables. From these experiments the correlation between input and output variables was determined. The best model is in agreement with the analysis of variance and Fischer's test. Graphs were obtained for both response and contour surfaces. In addition, the optimal point for the best model was determined by the Lagrange criterion, which corresponds to a feed rate (f) of 0.0880 mm rev-1 and the cutting speed (Vc) of 155 mm min.-1 , resulting in a minimum roughness average value (Ra) equals to 0.8916 μm.

Study on the Predictive of Dynamic Milling Force of Milling Process Based on Data Mining

“…Based on the connection function, Pei et al [8] analyzed the correlation of force signal, vibration signal and roughness signal in milling process, and got a better result. Rodrigues et al [9] applied correlation analysis to explore the degree of correlation between roughness and cutting speed and feed rate when turning 45-gauge steel in order to find the optimal configuration of the parameters. Thasthakeer et al [10] investigated the correlation between the variation of different parameters and the rate of change of cutting forces and surface roughness after machining.…”

The Predictive Research of Dynamic Milling Force Based on Data Mining

“…Based on the connection function, Pei Hongjie [8] and others analyzed the correlation of force signal, vibration signal and roughness signal in milling process, and got a better result. Jean Robert Pereira Rodrigues [9] et al applied correlation analysis to explore the degree of correlation between roughness and cutting speed and feed rate when turning 45-gauge steel in order to find the optimal configuration of the parameters. Ahmad [10] et al investigated the correlation between the variation of different parameters and the rate of change of cutting forces and surface roughness after machining and found that this correlation was higher under wet machining conditions.…”