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首页> 外文会议>International Conference on Advancess in Manufacturing and Materials Engineering >Effect and Optimization of Various Machine Process Parameters on the Surface Roughness in EDM for an EN19 Material using Response Surface Methodology
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Effect and Optimization of Various Machine Process Parameters on the Surface Roughness in EDM for an EN19 Material using Response Surface Methodology

机译：使用响应表面方法的EN19材料对EDM表面粗糙度的影响与优化

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摘要

In today's world the manufactured product not only requires high precision and quality but also the same is to be achieved in minimum time. This has given rise to a situation which requires the knowledge of optimum values of various input parameters to maximize or minimize a particular output. In the present work effort has been made to investigate the effect of various process parameters such as Pulse ON time, Pulse OFF time, Discharge Current and Voltage on the Surface Roughness for EN19 material in die sinking EDM process. EN 19 materials, due to presence of molybdenum and chromium, finds application in products experiencing high shock. By experimentation a relationship has been established between process parameters and responses in EDM using Response Surface Methodology. In this the main objective was to minimize the Surface Roughness resulting from the experimentation conducted as per L31 orthogonal array based on RSM. Experimental data obtained were statistically analyzed and the optimized sets of values of the various parameters were depicted. It was observed that with these values improvement in surface roughness were obtained. A confirmation test was carried out to check the deviation in surface roughness value of the predicted model with experimental data and it was observed that the error was within 0.02%.
机译：在今天的世界中，制造产品不仅需要高精度和质量，而且在最短的时间内也是如此。这引起了需要了解各种输入参数的最佳值的情况，以最大化或最小化特定输出。在目前的工作中，已经努力研究各种工艺参数，例如脉冲对时间，脉冲关闭时间，放电电流和电压上的ZH19材料的表面粗糙度上的脉冲截止值的影响。 EN 19材料由于存在钼和铬，在经历高震动的产品中找到应用。通过实验，使用响应表面方法在EDM中的过程参数和响应之间建立了关系。在此，主要目的是最小化根据基于RSM的L31正交阵列所进行的实验所产生的表面粗糙度。所获得的实验数据在统计学上分析，并描绘了各种参数的优化值组。观察到，通过这些值获得表面粗糙度的改善。进行确认测试以检查预测模型的偏差是否具有实验数据，观察到误差在0.02％以内。

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