In this study, Ti 6Al-4 V (grade 5) ELI alloy was machined with minimum energy and optimum surface quality and minimum tool wear. The appropriate cutting tool and suitable cutting parameters have been selected. As a result of the turning process, average surface roughness (Ra), tool wear and energy consumption were measured. The results have been analyzed by normality test, linear regression model, Taguchi analysis, ANOVA, Pareto graphics and multiple optimization method. It has been observed that high tool wear value increases Ra and energy consumption. In multiple optimization, it was concluded that it made predictions with 89,1% accuracy for Ra, 58,33% for tool wear, 96,75% for energy consumption. While the feed rate was the effective parameter for Ra and energy consumption, the effective parameter in tool wear was the cutting speed. Our study has revealed that by controlling energy consumption, surface quality can be maintained and tool wear can be controlled.

在这项研究中，Ti 6Al-4 V（5 级）ELI 合金以最小的能量和最佳的表面质量和最小的刀具磨损进行加工。已经选择了合适的切削刀具和合适的切削参数。作为车削过程的结果，测量了平均表面粗糙度 (Ra)、刀具磨损和能耗。采用正态性检验、线性回归模型、田口分析、方差分析、帕累托图和多重优化方法对结果进行了分析。已经观察到，高刀具磨损值会增加 Ra 和能耗。在多重优化中，得出的结论是，它对 Ra 的预测准确率为 89.1%，工具磨损的准确率为 58.33%，能源消耗的准确率为 96.75%。进给率是 Ra 和能耗的有效参数，而刀具磨损的有效参数是切削速度。