Analysis of MRR and SR with different electrode for SS 316 on Die-Sinking EDM using Taguchi Technique
Analysis of MRR and SR with different electrode for SS 316 on Die-Sinking EDM using Taguchi Technique
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发表时间：
2013-05
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通讯作者：
S. Choudhary;K. Kant;P. Saini
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作者：
S. Choudhary;K. Kant;P. Saini
新材料的发展呈现出巨大的增长，但主要的问题是，新材料的加工非常困难。因此，采用新的加工方法是必要的。电火花加工（EDM）是一种非传统和最流行的加工方法，用于制造模具，冲头和冲压工具，因为它能够产生复杂，复杂的形状和加工硬质材料。从工业的角度来看，不锈钢316是一种非常常用的材料，因为它具有耐腐蚀的特性。在实验过程中，电极材料，电流和脉冲时间作为变量的材料去除率和表面粗糙度的研究。实验中使用了三种不同的电极材料铜、黄铜和石墨，并使用电火花加工油作为电介质液。使用田口方法，L9正交表已被选定，并采取三个水平对应于每个变量。按照正交表中设计的一组实验进行实验。实验结果进行了分析，以及图形。为了更准确地分析输入参数的影响，计算了信噪比。结果发现，由于变量和因子数量较少，方差分析无法找到输出响应的关键显著性参数。利用信噪比值计算了MRR和SR的最佳值。
The development of new materials show the immense growth but the major problem, it is very difficult tomachine the newly developed materials. So it is necessary to adopt some new machining methods. Electrical Discharge Machining (EDM) is a non-traditional and most popular machining method to manufacture dies, punches and press tools because of its capability to produce complicated, intricate shapes and to machine hard materials. From the industrial point of view stainless steel 316 is a very commonly used material due to its property of resistant to corrosion. During experimentation, electrode material, current and pulseon time were taken as variables for the study of material removal rate and surface roughness. Three different electrode materials copper, brass and graphite were used with EDM oil as a dielectric fluid in the experiment. Using Taguchi method, L9 orthogonal array has been chosen and three levels corresponding to each of the variables are taken. Experiments have been performed as per the set of experiments designed in the orthogonal array. Results of experimentation were analyzed analytically as well as graphically. Signal to Noise ratio was calculated to analyze the effect of input parameter more accurately. It is found that ANOVA has unable to find the key significant parameters for the output response due to less number of variables and factors. The optimal value of MRR and SR were also calculated using their signal to noise ratio value.