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Analysed statistically Modelling and Optimization of Laser Machining by Response Surface Methodology

机译:响应面法对激光加工的统计建模与优化分析

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One of the important goals of this research is to predict a relationship between the process input parameters and resultants from surface roughness features through developing a laser cutting model. In most engineering applications, natural sciences and computing; statistical methods, which are one of mathematical branch are widely used for investigating the results. Laser cutting process of stainless steel (2205) is a machining process selected for this study. The technique which adopted here is a response surface methodology (RSM). The main portion for this study is the influence of cutting speed on surface quality. To study the model response, and for statistical approach with further prediction; a mathematical based model has been developed through regression analysis. It’s found that as one of the important results in this research, that cutting speed and surface roughness has a significant rule on the model response. To produce a good surface roughness, it’s approved that the high cutting speed connected with high power regardless of high pressure has a high influence on surface quality.
机译:这项研究的重要目标之一是通过开发激光切割模型来预测过程输入参数与表面粗糙度特征结果之间的关系。在大多数工程应用中,自然科学和计算机;统计方法是数学的一种分支,被广泛用于研究结果。不锈钢(2205)的激光切割工艺是本研究选择的机加工工艺。这里采用的技术是响应面方法(RSM)。这项研究的主要部分是切削速度对表面质量的影响。研究模型的响应,并为统计方法提供进一步的预测;通过回归分析开发了基于数学的模型。发现,作为这项研究的重要结果之一,切削速度和表面粗糙度对模型响应具有重要的影响。为了产生良好的表面粗糙度,已批准与高压无关的高切削速度和高功率对表面质量有很大影响。

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