Investigating Multiple Quality Objectives for Surface Roughness and Dimensional Accuracy of Carbon Steel Manufactured by Turn-Mill Multitasking Machining

Wei-Tai Huang, Ting-Yi Lee, J. Chou
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引用次数: 4

Abstract

This research in multiple quality objectives of the turning and milling multitasking machining is based on the Taguchi process and the fuzzy theory. These two methods can quickly find the best processing parameters to obtain the best surface roughness and dimensional accuracy and reduce the research cost and save research time. In this research, the Taguchi robust process $L9 (3^{4})$ orthogonal table was used to find the individual optimized process parameters. The control factors used were spindle speed (RPM), feed (mm/min), and C-axis brake pressure (kg/$cm^{2})$.), the axial cutting depth, and then taking the surface roughness and dimensional accuracy as the characteristic indicators, and then the respective signal-to-noise ratio (S/N) is grayed out according to the experimental sequence to generate normalization, and the gray correlation coefficient is obtained. Further, a Multiple Performance Characteristic Index (MPCI) is obtained. The research results clearly demonstrated that the overall results of the process optimum parameters obtained by using the measurement indicators of multiple quality characteristics prevail the results of the individual optimized process parameters.
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车铣多任务加工碳钢表面粗糙度和尺寸精度的多重质量目标研究
基于田口法和模糊理论,对车铣多任务加工的多质量目标进行了研究。这两种方法可以快速找到最佳的加工参数,获得最佳的表面粗糙度和尺寸精度,降低了研究成本,节省了研究时间。在本研究中,采用田口鲁棒过程$L9(3^{4})$正交表来寻找各个优化的工艺参数。所采用的控制因素为主轴转速(RPM)、进给量(mm/min)、c轴制动压力(kg/$cm^{2})、轴向切削深度,然后以表面粗糙度和尺寸精度为特征指标,根据实验顺序对各自的信噪比(S/N)进行灰化处理,生成归一化,得到灰色相关系数。进一步,得到了多性能特征指数(MPCI)。研究结果清楚地表明,采用多个质量特性测量指标得到的工艺优化参数的总体结果优于单个工艺参数的优化结果。
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