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

机译:调查由磨机多任务加工制造的碳钢表面粗糙度和尺寸精度的多种质量目标

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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(34) 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/cm2), 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.
机译:该研究的转弯和铣削多任务加工的多种质量目标是基于Taguchi过程和模糊理论。这两种方法可以快速找到最佳的处理参数,以获得最佳表面粗糙度和尺寸精度,降低研究成本并节省研究时间。在本研究中,Taguchi强大的过程L9(3 4 )正交表用于找到个体优化的过程参数。使用的控制因子是主轴速度(rpm),进料(mm / min)和c轴制动压力(kg / cm 2 ),轴向切割深度,然后采用表面粗糙度和尺寸精度作为特征指示器,然后根据实验序列产生相应的信噪比(S / N)以产生归一化,以及获得灰色相关系数。此外,获得多个性能特征索引(MPCI)。研究结果清楚地证明,通过使用多种质量特性的测量指示器获得的过程最佳参数的总体结果占各个优化工艺参数的结果。

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