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基于田口方法和灰色关联分析的碳化硅超声抛光多目标优化

Multi-Objective Optimization in Ultrasonic Polishing of Silicon Carbide via Taguchi Method and Grey Relational Analysis.

作者信息

Chen Xin, Xu Shucong, Meng Fanwei, Yu Tianbiao, Zhao Ji

机构信息

School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110819, China.

School of Materials Science and Engineering, Harbin Institute of Technology, Harbin 150001, China.

出版信息

Materials (Basel). 2023 Aug 18;16(16):5673. doi: 10.3390/ma16165673.

Abstract

As high-level equipment and advanced technologies continue toward sophistication, ultrasonic technology is extensively used in the polishing process of difficult-to-process materials to achieve efficiently smooth surfaces with nanometer roughness. The polishing of silicon carbide, an indispensable difficult-to-machine optical material, is extremely challenging due to its high hardness and good wear resistance. To overcome the current silicon carbide (SiC) ultrasonic polishing (UP) process deficiencies and strengthen the competitiveness of the UP industry, the multi-objective optimization based on the Taguchi-GRA method for the UP process with SiC ceramic to obtain the optimal process parameter combination is a vital and urgently demanded task. The orthogonal experiment, analysis of variance, grey relational analysis (GRA), and validation were performed to optimize the UP schemes. For a single objective of roughness and removal rate, the influence degree is abrasive size > preloading force > abrasive content > spindle speed > feed rate, and spindle speed > abrasive size > feed rate > preloading force > abrasive content, respectively. Moreover, the optimal process combination integrating these two objectives is an abrasive content of 14 wt%, abrasive size of 2.5 μm, preloading force of 80 N, spindle speed of 8000 rpm, and feed rate of 1 mm/s. The optimized workpiece surface morphology is better, and the roughness and removal rate are increased by 7.14% and 28.34%, respectively, compared to the best orthogonal group. The Taguchi-GRA method provides a more scientific approach for evaluating the comprehensive performance of polishing. The optimized process parameters have essential relevance for the ultrasonic polishing of SiC materials.

摘要

随着高端设备和先进技术不断走向精密化,超声技术在难加工材料的抛光过程中得到广泛应用,以实现具有纳米粗糙度的高效光滑表面。碳化硅作为一种不可或缺的难加工光学材料,由于其高硬度和良好的耐磨性,其抛光极具挑战性。为克服当前碳化硅(SiC)超声抛光(UP)工艺的不足,增强UP行业的竞争力,基于田口-灰色关联分析(GRA)方法对SiC陶瓷的UP工艺进行多目标优化,以获得最佳工艺参数组合,是一项至关重要且迫切需要的任务。通过进行正交试验、方差分析、灰色关联分析(GRA)和验证来优化UP方案。对于粗糙度和去除率这两个单一目标,影响程度分别为磨料粒度>预紧力>磨料含量>主轴转速>进给速度,以及主轴转速>磨料粒度>进给速度>预紧力>磨料含量。此外,综合这两个目标的最佳工艺组合是磨料含量为14 wt%、磨料粒度为2.5μm、预紧力为80 N、主轴转速为8000 rpm以及进给速度为1 mm/s。与最佳正交组相比,优化后的工件表面形貌更佳,粗糙度和去除率分别提高了7.14%和28.34%。田口-GRA方法为评估抛光的综合性能提供了一种更科学的方法。优化后的工艺参数对SiC材料的超声抛光具有重要意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/abbc/10456480/9dbf35b6c4d9/materials-16-05673-g001.jpg

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