Das Layatitdev, Nayak Rakesh, Saxena Kuldeep K, Nanda Jajneswar, Jena Shakti Prasad, Behera Ajit, Sehgal Shankar, Prakash Chander, Dixit Saurav, Abdul-Zahra Dalael Saad
Department of Mechanical Engineering, VSSUT Burla, Burla 768018, India.
Department of Mechanical Engineering, GLA University, Mathura 281406, India.
Materials (Basel). 2022 Jul 7;15(14):4765. doi: 10.3390/ma15144765.
This paper shows the novel approach of Taguchi-Based Grey Relational Analysis of Ti6Al4V Machining parameter. Ti6Al4V metal matrix composite has been fabricated using the powder metallurgy route. Here, all the components of TI6Al4V machining forces, including longitudinal force (F), radial force (F), tangential force (F), surface roughness and material removal rate (MRR) are measured during the facing operation. The effect of three process parameters, cutting speed, tool feed and cutting depth, is being studied on the matching responses. Orthogonal design of experiment (Taguchi L9) has been adopted to execute the process parameters in each level. To validate the process output parameters, the Grey Relational Analysis (GRA) optimization approach was applied. The percentage contribution of machining parameters to the parameter of response performance was interpreted through variance analysis (ANOVA). Through the GRA process, the emphasis was on the fact that for TI6Al4V metal matrix composite among all machining parameters, tool feed serves as the highest contribution to the output responses accompanied by the cutting depth with the cutting speed in addition. From optimal testing, it is found that for minimization of machining forces, maximization of MRR and minimization of Ra, the best combinations of input parameters are the 2nd stage of cutting speed (175 m/min), the 3rd stage of feed (0.25 mm/edge) as well as the 2nd stage of cutting depth (1.2 mm). It is also found that hardness of Ti6Al4V MMC is 59.4 HRA and composition of that material remain the same after milling operation.
本文展示了基于田口方法的Ti6Al4V加工参数灰色关联分析的新方法。Ti6Al4V金属基复合材料采用粉末冶金路线制备。在此,在端面车削操作过程中测量了Ti6Al4V加工力的所有分量,包括纵向力(F)、径向力(F)、切向力(F)、表面粗糙度和材料去除率(MRR)。研究了切削速度、进给量和切削深度这三个工艺参数对匹配响应的影响。采用实验的正交设计(田口L9)来执行每个水平的工艺参数。为了验证工艺输出参数,应用了灰色关联分析(GRA)优化方法。通过方差分析(ANOVA)解释了加工参数对响应性能参数的贡献率。通过GRA过程,重点在于对于Ti6Al4V金属基复合材料,在所有加工参数中,进给量对输出响应的贡献最大,其次是切削深度,切削速度的贡献最小。通过优化测试发现,为了最小化加工力、最大化MRR和最小化Ra,输入参数的最佳组合是切削速度的第二阶段(175米/分钟)、进给量的第三阶段(0.25毫米/刃)以及切削深度的第二阶段(1.2毫米)。还发现Ti6Al4V金属基复合材料的硬度为59.4 HRA,铣削操作后该材料的成分保持不变。