This study aims to examine the usability of environmentally harmless vegetable oil in the minimum quantity of lubrication(MQL)system in face milling of AISI O2 steel and to optimize the cutting parameters by different...This study aims to examine the usability of environmentally harmless vegetable oil in the minimum quantity of lubrication(MQL)system in face milling of AISI O2 steel and to optimize the cutting parameters by different statistical methods.Vegetable oil was preferred as cutting fluid,and Taguchi method was used in the preparation of the test pattern.After testing with the prepared test pattern,cutting performance in all parameters has been improved according to dry conditions thanks to the MQL system.The highest tool life was obtained by using cutting parameters of 7.5 m cutting length,100 m/min cutting speed,100 mL/h MQL flow rate and 0.1 mm/tooth feed rate.Optimum cutting parameters were determined according to the Taguchi analysis,and the obtained parameters were confirmed with the verification tests.In addition,the optimum test parameter was determined by applying the gray relational analysis method.After using ANOVA analysis according to the measured surface roughness and cutting force values,the most effective cutting parameter was observed to be the feed rate.In addition,the models for surface roughness and cutting force values were obtained with precisions of 99.63%and 99.68%,respectively.Effective wear mechanisms were found to be abrasion and adhesion.展开更多
In the present study,the effect of reduction of cutting fluid consumption on the surface quality and tool wear was studied.Mathematical models were developed to predict the surface roughness using response surface met...In the present study,the effect of reduction of cutting fluid consumption on the surface quality and tool wear was studied.Mathematical models were developed to predict the surface roughness using response surface methodology(RSM).Analysis of variance(ANOVA)was used to investigate the significance of the developed regression models.The results showed that the coefficient of determination values(R^2)for the developed models was 97.46%for dry,89.32%for flood mode(FM),and 99.44%for MQL,showing the high accuracy of fitted models.Also,under the minimum quantity lubrication(MQL)condition,the surface roughness improved by 23%−44%and 19%−41%compared with dry and FM,respectively,and the SEM images of machined surface proved the statement.The prepared SEM images of tool rake face also showed a considerable decrease in adhesion wear.Built-up edge and built-up layer were the two main products of the adhesion wear,and energy-dispersive X-ray spectroscopy(EDX)analysis of specific points on the tool faces helped to discover the chemical compositions of adhered materials.By changing dry and FM to MQL mode,dominant mechanism of tool wear in machining aluminum alloy was significantly decreased.Breakage wear that led to early failure of cutting edge was also controlled by MQL technique.展开更多
文摘This study aims to examine the usability of environmentally harmless vegetable oil in the minimum quantity of lubrication(MQL)system in face milling of AISI O2 steel and to optimize the cutting parameters by different statistical methods.Vegetable oil was preferred as cutting fluid,and Taguchi method was used in the preparation of the test pattern.After testing with the prepared test pattern,cutting performance in all parameters has been improved according to dry conditions thanks to the MQL system.The highest tool life was obtained by using cutting parameters of 7.5 m cutting length,100 m/min cutting speed,100 mL/h MQL flow rate and 0.1 mm/tooth feed rate.Optimum cutting parameters were determined according to the Taguchi analysis,and the obtained parameters were confirmed with the verification tests.In addition,the optimum test parameter was determined by applying the gray relational analysis method.After using ANOVA analysis according to the measured surface roughness and cutting force values,the most effective cutting parameter was observed to be the feed rate.In addition,the models for surface roughness and cutting force values were obtained with precisions of 99.63%and 99.68%,respectively.Effective wear mechanisms were found to be abrasion and adhesion.
文摘In the present study,the effect of reduction of cutting fluid consumption on the surface quality and tool wear was studied.Mathematical models were developed to predict the surface roughness using response surface methodology(RSM).Analysis of variance(ANOVA)was used to investigate the significance of the developed regression models.The results showed that the coefficient of determination values(R^2)for the developed models was 97.46%for dry,89.32%for flood mode(FM),and 99.44%for MQL,showing the high accuracy of fitted models.Also,under the minimum quantity lubrication(MQL)condition,the surface roughness improved by 23%−44%and 19%−41%compared with dry and FM,respectively,and the SEM images of machined surface proved the statement.The prepared SEM images of tool rake face also showed a considerable decrease in adhesion wear.Built-up edge and built-up layer were the two main products of the adhesion wear,and energy-dispersive X-ray spectroscopy(EDX)analysis of specific points on the tool faces helped to discover the chemical compositions of adhered materials.By changing dry and FM to MQL mode,dominant mechanism of tool wear in machining aluminum alloy was significantly decreased.Breakage wear that led to early failure of cutting edge was also controlled by MQL technique.
