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Optimization of MRR, TWR and surface roughness of EDMed D2 Steel using an integrated approach of RSM, GRA and Entropy measutement method

机译:RSM,GRA和熵测法相结合的方法优化了D2钢的MRR,TWR和表面粗糙度

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In this research, a hybrid optimization approach is proposed for the determination of the optimal process parameters that maximizes the material removal rate, minimize surface roughness & the tool wear rate. Three input parameters namely pulse current (Ip), pulse duration (Ton) & pulse off time (Toff) of electrical discharge machining were considered for this analysis. The experiments were planned as per response surface methodology and subsequently gray relational analysis has been used to optimize the aforesaid response and finally the weight of the responses was determined by the entropy measurement method. Analysis of variance is used to find the effect of input parameters on the responses and found that Ton was the most influencing parameter followed by Ip and Toff in EDM of D2 steel. The R2 value for the grey relational grade model was 0.919. These results provide useful information about how to control the responses and ensure higher productivity, high-accuracy and higher surfaces-quality surfaces. This method is simple with easy operability. The assessment outcome provides a scientific reference to obtain the minimal condition of surface integrity, and they were found to be a pulse current of 5A, pulse duration of 60 µs, and pause time of 45 µs.
机译:在这项研究中,提出了一种用于确定最佳工艺参数的混合优化方法,该方法可最大程度地提高材料去除率,最小化表面粗糙度和刀具磨损率。该分析考虑了三个输入参数,即放电加工的脉冲电流(Ip),脉冲持续时间(Ton)和脉冲关闭时间(Toff)。根据响应面方法对实验进行了规划,随后通过灰色关联分析对上述响应进行了优化,最后通过熵测量法确定了响应的权重。方差分析用于发现输入参数对响应的影响,并发现在D2钢的EDM中,Ton是影响最大的参数,其次是Ip和Toff。灰色关联等级模型的R2值为0.919。这些结果提供了有关如何控制响应并确保更高生产率,高精度和更高表面质量的表面的有用信息。该方法简单易操作。评估结果为获得最小的表面完整性条件提供了科学依据,发现它们的脉冲电流为5A,脉冲持续时间为60 µs,暂停时间为45 µs。

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