The present research study was aimed at studying the impact of machining parameters on grain size alterations in machining of Ti6Al4V alloy using finite element analysis (FEA) based on the Johnson-Mehl-Avrami-Kolmogorov (JMAK) recrystallization model. The machining parameters consisted of both cutting conditions and tool geometry including cutting speed, feed rate, tool edge radius and rake angle. Three series of JMAK constants were used in the simulations and the degree of accuracy of the obtained results were compared. Finite element (FE) simulations were conducted for machining conditions designed using a D-optimal Design of Experiment (DoE). Analysis of Variance (ANOVA) was carried out to identify the most effective machining parameters on the responses of average grain size (AGS), machining temperature (MT), cutting force (CF), and feed force (FF). Next, Response Surface Method (RSM) was used to predict regression models of AGS, MT, CF, and FF. The optimal values of machining parameters were obtained to improve AGS, MT, CF, and FF. The ANOVA results showed that rake angle and cutting speed were, respectively, the most and least significant parameters affecting AGS in the design space. Rake angle was the most effective parameter influencing all of the responses. The single-criterion optimization of AGS provided a small improvement in AGS with a high increase in material removal rate (MRR). The results of the multi-criteria optimization of AGS, MT, CF, and FF demonstrated that machining of Ti6Al4V alloy with a tool having a medium cutting edge radius and high positive rake angle at a medium cutting speed and a low feed rate in the design space produced finer grains along with reduced CF and FF and an unchanged MT.

本研究旨在利用基于Johnson-Mehl-Avrami-Kolmogorov（JMAK）重结晶模型的有限元分析（FEA）研究加工参数对Ti6Al4V合金加工中晶粒尺寸变化的影响。加工参数包括切削条件和刀具几何形状，包括切削速度，进给速度，刀刃半径和前角。在仿真中使用了三个系列的JMAK常数，并比较了所获得结果的准确性。对使用D最佳实验设计（DoE）设计的加工条件进行了有限元（FE）模拟。进行方差分析（ANOVA），以根据平均晶粒尺寸（AGS），加工温度（MT），切削力（CF），和进给力（FF）。接下来，使用响应面法（RSM）来预测AGS，MT，CF和FF的回归模型。获得加工参数的最佳值以改善AGS，MT，CF和FF。方差分析结果表明，前角和切削速度分别是影响设计空间中AGS的最高和最低参数。前角是影响所有响应的最有效参数。AGS的单准则优化使AGS的改进很小，同时材料去除率（MRR）大大提高。AGS，MT，CF，