Research on machining continues increasingly today. The effects of independent variables (cutting speed, feed rate, cutting depth) on dependent variables (material removal rate (MRR), average surface roughness (Ra), sound intensity, energy consumption, and vibration) are among the most researched topics in machining. It is also important to achieve optimum results with low cost and time savings in machining. In this study, titanium alloy TC4 material was turned on CNC lathe. Taguchi L16 mixed level design was used in experimental design. MRR, Ra, sound intensity, energy consumption, and vibration values were measured for the determined cutting parameters. The measured values were researched experimentally and statistically. Effective parameters were determined. It was concluded that the cutting parameter that has the greatest effect on MRR, Ra, energy consumption, and vibration is the feed rate. In addition, the depth of cut was the parameter that most affected the sound intensity. Control experiments were carried out after determining the optimum machining parameters. With multiple optimization, the predictions were made with approximately 89% accuracy (92.75% for MRR, 92.49% for Ra, 89.45% for sound intensity, 92.70% for energy consumption, 96.16% for vibration).

中文翻译：

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TC4钛合金可加工性MRR、表面粗糙度、声强、能耗、振动值的多重优化分析

今天，对机械加工的研究越来越多。自变量（切削速度、进给速度、切削深度）对因变量（材料去除率 (MRR)、平均表面粗糙度 (Ra)、声强、能耗和振动）的影响是加工中研究最多的课题之一. 以低成本和节省加工时间的方式获得最佳结果也很重要。在这项研究中，钛合金 TC4 材料在数控车床上车削。田口升16实验设计采用混合水平设计。针对确定的切削参数测量 MRR、Ra、声强、能耗和振动值。对测量值进行了实验和统计研究。确定有效参数。得出的结论是，对 MRR、Ra、能耗和振动影响最大的切削参数是进给速度。此外，切深是影响声强的最大参数。在确定最佳加工参数后进行控制实验。通过多次优化，预测的准确率约为 89%（MRR 为 92.75%，Ra 为 92.49%，声强为 89.45%，能耗为 92.70%，振动为 96.16%）。