In this work, it is aimed to study the effects of dry machining and minimum quantity lubrication application on machinability in turning AISI 4140 steel by utilizing different cutting parameters. Also, this study contains effects and optimization of cutting conditions (dry and minimum quantity lubricating), feed rate, and cutting speed on surface roughness (Ra) and main cutting forces (Fc) determined by employing the Taguchi method. At the end of experiments, it was established that compared to dry machining operations, minimum quantity lubricating significantly reduced cutting tool wear, while Fc and Ra decreased in general. Analyses of variance, regression analysis, signal-to-noise ratio, and orthogonal array were employed to analyze the effects and contributions of independent variables on dependent variables. The optimum levels of the dependent variables for reducing Fc and Ra using signal-to-noise rates were established. According to signal-to-noise ratios, minimum quantity lubricating had a more important effect on Fc and Ra than dry machining. The optimal conditions for Fc and Ra were at 0.16 mm/rev feed rate, 125 m/min cutting speed at minimum quantity lubricating. Analysis of variance results demonstrated that the feed rate is the most influential independent variable on Fc (93.976 %) and Ra (89.352 %). Validation test results exhibited that the Taguchi method and regression analysis were highly achieved methods in the optimization of independent variables for dependent variables. Taguchi optimization technique and regression analysis obtained from Fc ([Formula: see text] = 0.972 and [Formula: see text] = 0.997) and Ra ([Formula: see text] = 0.985 and [Formula: see text] = 0.996) measurements match really well with the experimental data.
The applications of cutting fluids in metal cutting have negative results such as increasing machining cost and polluting environment, water and soil pollution stemming from wastes. Therefore, use of Minimum Quantity Lubrication (MQL) technique is generally preferred since it not only gives better results but also exhibits favorable influences on environmental pollution and human health. The objective of this experimental and statistical study is to investigate the effects of both machining conditions (MQL, Dry and Wet) and cutting parameters on sustainability and machinability. Another aim of this study is to establish significance of control factors on the response values by using signal to noise (S/N) ratio, Taguchi orthogonal array, analyses of variance (ANOVA), linear and quadratic equations and to select optimal cutting parameters as well. Also, the Pugh matrix approach was utilized to compare different coolant types in terms of sustainable manufacturing. According to the experimental results, it was found that MQL cutting significantly decreased cutting tool wear when compared to dry and wet cutting, while it reduced main cutting force (Fc) and surface roughness (Ra) in general. The results of S/N ratios showed that MQL had more significant effect on Ra and Fc than wet and dry cutting. The values of optimal cutting condition were obtained as 0.16 mm/rev and 125 m/min for feed rate and cutting speed in MQL machining, respectively. According to the experimental results, it was found that MQL cutting, when compared dry and wet cutting, decreased by average 25%dry, 5%wet, 15%dry, 2%wet, 44%dry and 9%wet in terms of cutting tool wear, Fc and Ra, respectively. According to ANOVA, feed rate is the most effective factor on Fc and Ra values. It was found that the results estimated for Fc and Ra values using Taguchi method, linear and quadratic equations are quite successful within 3% deviation. According to Pugh matrix approach assessment results, MQL machining was superior to dry and wet machining in terms of sustainability and cleaner production.
In this study, the effects of cutting speed, feed rate and minimum quantity lubrication (MQL), frequently employed in machining applications, on main cutting force (Fc) and average surface roughness (Ra), resulting from turning AISI 4140, were investigated. For this purpose, analyses for Fc and Ra were performed utilizing Box-Behnken model. By using experimental parameters, the efficiency and the changes of the parameters on Fc and Ra were examined with the help of 13 experiments. In addition, the effectiveness of design models was investigated by creating different design models. The high success rate modelling for Fc and Ra was realized with 99% success as a result of analyses conducted according to Box-Behnken methods (Box-Behnken, Box-Behnken-Stepwise, Box-Behnken-Backward and Box-Behnken-Forward). The most effective parameter on Fc and Ra was found to be the feed rate according to analysis of variance (ANOVA). It was demonstrated that the estimations on the created Box-Behnken model were quite successful on the data initially entered into the system; and that R2 values obtained for Fc and Ra were 0.999 and 0.996, respectively. It was determined that optimum parameters for Fc were feed rate 0.25 mm/rev, cutting speed 125 m/min and cutting condition MQL2 ml/min, while they were feed rate 0.25 mm/rev, cutting speed 125 m/min and cutting condition MQL1 ml/min for Ra.
Bu makaleye şu şekilde atıfta bulunabilirsiniz(To cite to this article): Gürbüz G., Gönülaçar Y. E., "Farklı kesme parametreleri ve MQL debilerinde elde edilen deneysel değerlerin S/N oranları ve YSA ile analizi", Politeknik Dergisi, *(*): *, (*).
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