Optimization of magnetic compound fluid polishing process parameters for PMMA workpieces based on grey relational analysis

WANG Youliang; GAO Xichun; ZHANG Wenjuan

doi:10.13394/j.cnki.jgszz.2023.0282

Volume 45 Issue 1

Mar. 2025

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WANG Youliang, GAO Xichun, ZHANG Wenjuan. Optimization of magnetic compound fluid polishing process parameters for PMMA workpieces based on grey relational analysis[J]. Diamond & Abrasives Engineering, 2025, 45(1): 134-142. doi: 10.13394/j.cnki.jgszz.2023.0282

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WANG Youliang, GAO Xichun, ZHANG Wenjuan. Optimization of magnetic compound fluid polishing process parameters for PMMA workpieces based on grey relational analysis[J]. Diamond & Abrasives Engineering, 2025, 45(1): 134-142. doi: 10.13394/j.cnki.jgszz.2023.0282

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Optimization of magnetic compound fluid polishing process parameters for PMMA workpieces based on grey relational analysis

doi: 10.13394/j.cnki.jgszz.2023.0282

1.
School of Mechanical and Electrical Engineering, Lanzhou University of Technology, Lanzhou 730000, China
2.
State Key Laboratory of Advanced Processing and Recycling of Nonferrous Metals, Lanzhou University of Technology, Lanzhou 730000, China

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Received Date: 2023-12-28
Accepted Date: 2024-03-13
Rev Recd Date: 2024-03-05

Available Online: 2025-03-24

Abstract

Abstract

Objectives MCF polishing technology has become an advanced ultra-precision machining method. To address the issue of different process parameters in achieving optimal surface quality or maximum processing efficiency in MCF polishing technology, it is necessary to accurately control the range of each process parameter and deeply understand the impact of different process parameters on MCF polishing performance. Methods The process parameters of the MCF polishing tool are optimized based on grey relation analysis (GRA) to meet the requirements of minimum surface roughness while improving material removal efficiency. Under the given experimental conditions, it is verified that the optimized MCF polishing tool has excellent polishing performance, and the mechanism of the influences of various process parameters on the polishing performance of the MCF polishing tool is analyzed in detail. Firstly, a three-factor four-level PMMA workpiece polishing experiment is designed using the orthogonal test method, and the influence mechanism of each factor on MCF polishing performance is analyzed. Afterwards, the GRA method is used to optimize multi-objective factors, and the optimization scheme of process parameters with the best polishing effect is determined. Finally, the optimized process parameters are used to verify the polishing of the workpiece, and the surface morphology and the contour of the workpiece are obtained. Results When the magnetic induction intensity B = 0.5 T, the diameter of carbonyl iron powder D_CIP = 7 μm, and the diameter of abrasive particle D_AP = 3 μm, the surface finishing ability of the MCF polishing tool is the best. When the magnetic induction intensity B = 0.5 T, the diameter of carbonyl iron powder D_cip = 7 μm, and the diameter of abrasive particle D_AP = 7 μm, the material removal efficiency of the MCF polishing tool is the highest. The magnetic induction intensity has the greatest impact on the polishing quality and the material removal efficiency of the MCF polishing tool, followed by the diameter of carbonyl iron powder, while the effect of the diameter of the abrasive particle is relatively small. During the polishing process, abrasive particle with a smaller diameter make the surface of the workpiece smoother, but the processing efficiency is lower. The polishing effect of abrasive particles with a larger diameter is uneven, but the processing efficiency is higher. The grey correlation degree of each orthogonal experimental group is calculated based on GRA, and the multi-objective factors were optimized to obtain the optimal combination of process parameters, comprehensively considering the workpiece surface quality and processing efficiency, that is, when the magnetic induction intensity B = 0.5 T, the diameter of carbonyl iron powder D_CIP = 7 μm, and the diameter of abrasive particle D_AP = 3 μm, the MCF polishing tools achieve the best comprehensive polishing performance. Under the given conditions, the PMMA workpiece is polished by using the optimal process parameter, reducing the surface roughness of the workpiece from 477 nm to 14 nm, with a surface roughness reduction rate of 97.06%, which is 3.49 percentage points higher than that before optimization. The material removal rate reaches 2.088×10⁸ $ \mathrm{\mu } $m³/min, which is 3.5% higher than that without optimization. Conclusions The process parameter combination obtained through GRA optimization not only meets the requirements for high surface quality of the workpiece, but also significantly improves the material removal rate of the MCF polishing tool. After GRA optimization, the polishing ability of the MCF polishing tool is significantly enhanced.
- magnetic compound fluid,
- grey relational analysis,
- process parameters,
- surface roughness,
- material removal rate

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References(20)

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Optimization of magnetic compound fluid polishing process parameters for PMMA workpieces based on grey relational analysis

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