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Optimization of machining parameters on temperature rise in end milling of Al 6063 using response surface methodology and genetic algorithm

机译:基于响应面法和遗传算法的铝6063立铣刀温升加工参数优化

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摘要

This present study focused on the effect of machining parameters such as helix angle of cutter, spindle speed, feed rate, axial and radial depth of cut on temperature rise in end milling. A prediction model of the temperature rise was developed using response surface methodology. The experiments were conducted on Al 6063 by high-speed steel end mill cutter based on central composite rotatable designs consisting of 32 experiments. The temperature rise was measured using K-type thermocouple. The adequacy of the model was verified using analysis of variance. The given model is utilized to analyze direct and interaction effect of the machining parameters with temperature rise. The optimization of machining process parameters to obtain minimum temperature rise was done using genetic algorithms. A source code using C language was developed to do the optimization. The obtained optimal machining parameters gave a value of 0.173℃ for minimum temperature rise.
机译:本研究的重点是诸如立铣刀的螺旋角,主轴转速,进给速度,切削轴向和径向切削深度等加工参数对立铣刀中温度升高的影响。使用响应面方法开发了温度升高的预测模型。实验是在Al 6063高速钢立铣刀上进行的,该刀具基于32个实验组成的中心复合可旋转设计。使用K型热电偶测量温度升高。使用方差分析验证了模型的充分性。利用给定的模型分析了加工参数随温度升高的直接影响和相互作用。使用遗传算法对加工工艺参数进行了优化以获得最低的温度升高。开发了使用C语言的源代码来进行优化。获得的最佳加工参数给出的最小温升值为0.173℃。

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