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首页> 外文期刊>Journal of Material Sciences & Engineering >Optimization of Sustainable Cutting Conditions in Turning Carbon Steel by CNC Turning Machine
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Optimization of Sustainable Cutting Conditions in Turning Carbon Steel by CNC Turning Machine

机译:数控车床对车削碳钢的可持续切削条件的优化

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The current study aims to find the optimum cutting parameters in turning process without using cutting fluids (dry cutting condition) towards sustainable manufacturing. Where the power consumption and environmental pollution increase due to increase of the machining operations in manufacturing field, so to save energy and environment and reduce cost it is important to adopt sustainability in machining processes. The experimental work in this study involves the preparation to a number of experiments on AISI 1045 carbon steel to collect the necessary data for implementing optimization process. The experiments were conducted by changing levels of cutting parameters (spindle speed, feed rate and cutting depth) in CNC turning machine. Surface roughness of the workpiece has been depended as a quality indicator. In addition, the temperature of cutting tool has been recorded during machining the work pieces in order to control the temperature of cutting process. Theoretically, empirical equations for temperature of cutting tool and surface roughness of the work piece have been discovered. By using Genetic Algorithm technique these equations have been used to find the optimum of cutting parameters spindle speed, feed rate and depth of cut. The optimum values that obtained by using Genetic Algorithm which achieve sustainable cutting were spindle speed 588.96 rpm, depth of cut 0.50 mm and feed rate 64.55 mm/min in order to have the optimum of surface roughness in low cutting temperature.
机译:当前的研究旨在在不使用切削液(干切削条件)的情况下,在车削过程中找到最佳切削参数,以实现可持续生产。由于制造领域中机械加工的增加而导致功耗和环境污染的增加,因此为了节省能源和环境并降低成本,在机械加工过程中采用可持续性很重要。本研究中的实验工作涉及为AISI 1045碳钢准备许多实验,以收集实施优化过程所需的数据。通过改变数控车床中切削参数(主轴转速,进给速度和切削深度)的水平进行实验。工件的表面粗糙度已被视为质量指标。另外,在加工工件期间已记录了切削工具的温度,以控制切削过程的温度。从理论上讲,已经发现了刀具温度和工件表面粗糙度的经验公式。通过使用遗传算法技术,这些方程式已被用于寻找最佳的切削参数,主轴转速,进给速度和切削深度。通过遗传算法获得的可持续切削的最佳值为主轴转速588.96 rpm,切削深度0.50 mm和进给速度64.55 mm / min,以便在低切削温度下获得最佳的表面粗糙度。

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