Optimization of Shear-Thickening Polishing Parameters for Optical Glass Based on Grey Relational Analysis
This study aimed to enhance the efficiency and surface quality of shear-thickening polishing (STP) for optical glass through optimizing the polishing parameters. Sixteen orthogonal experiments were conducted to assess the effects of polishing speed (<inline-formula><math xmlns="http://...
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2025-01-01
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author | Yunxiao Han Yangsi Yang Binghai Lyu Wei Hang Xu Wang Julong Yuan |
author_facet | Yunxiao Han Yangsi Yang Binghai Lyu Wei Hang Xu Wang Julong Yuan |
author_sort | Yunxiao Han |
collection | DOAJ |
description | This study aimed to enhance the efficiency and surface quality of shear-thickening polishing (STP) for optical glass through optimizing the polishing parameters. Sixteen orthogonal experiments were conducted to assess the effects of polishing speed (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>V</mi></mrow></semantics></math></inline-formula>), angle (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>θ</mi></mrow></semantics></math></inline-formula>), and slurry concentration (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>C</mi></mrow></semantics></math></inline-formula>) on the material removal rate (MRR) and surface roughness (Ra). Grey relational analysis simplified the multi-objective optimization problem, and a regression model was formulated to determine the optimal combination of polishing parameters. The results indicate that slurry concentration has the most significant impact on the optimization objective, followed by polishing angle, whereas polishing speed has the least effect. Under the optimal combination of polishing parameters—polishing speed of 70 rpm, polishing angle of 70°, and slurry concentration of 12%—the surface roughness (Ra) of optical glass was significantly reduced to 8.23 nm during a 20 min polishing process, while the material removal rate (MRR) reached 813.63 nm/min. Shear-thickening polishing under the optimized process parameters can effectively remove scratches from the workpiece surface and significantly enhance surface quality. |
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institution | Kabale University |
issn | 2075-1702 |
language | English |
publishDate | 2025-01-01 |
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spelling | doaj-art-c2fa3146584d40348819b40457e305712025-01-24T13:39:14ZengMDPI AGMachines2075-17022025-01-011314010.3390/machines13010040Optimization of Shear-Thickening Polishing Parameters for Optical Glass Based on Grey Relational AnalysisYunxiao Han0Yangsi Yang1Binghai Lyu2Wei Hang3Xu Wang4Julong Yuan5College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaThis study aimed to enhance the efficiency and surface quality of shear-thickening polishing (STP) for optical glass through optimizing the polishing parameters. Sixteen orthogonal experiments were conducted to assess the effects of polishing speed (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>V</mi></mrow></semantics></math></inline-formula>), angle (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>θ</mi></mrow></semantics></math></inline-formula>), and slurry concentration (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>C</mi></mrow></semantics></math></inline-formula>) on the material removal rate (MRR) and surface roughness (Ra). Grey relational analysis simplified the multi-objective optimization problem, and a regression model was formulated to determine the optimal combination of polishing parameters. The results indicate that slurry concentration has the most significant impact on the optimization objective, followed by polishing angle, whereas polishing speed has the least effect. Under the optimal combination of polishing parameters—polishing speed of 70 rpm, polishing angle of 70°, and slurry concentration of 12%—the surface roughness (Ra) of optical glass was significantly reduced to 8.23 nm during a 20 min polishing process, while the material removal rate (MRR) reached 813.63 nm/min. Shear-thickening polishing under the optimized process parameters can effectively remove scratches from the workpiece surface and significantly enhance surface quality.https://www.mdpi.com/2075-1702/13/1/40optical glassshear-thickening polishingorthogonal experimentsgrey relational analysisparameter optimization |
spellingShingle | Yunxiao Han Yangsi Yang Binghai Lyu Wei Hang Xu Wang Julong Yuan Optimization of Shear-Thickening Polishing Parameters for Optical Glass Based on Grey Relational Analysis Machines optical glass shear-thickening polishing orthogonal experiments grey relational analysis parameter optimization |
title | Optimization of Shear-Thickening Polishing Parameters for Optical Glass Based on Grey Relational Analysis |
title_full | Optimization of Shear-Thickening Polishing Parameters for Optical Glass Based on Grey Relational Analysis |
title_fullStr | Optimization of Shear-Thickening Polishing Parameters for Optical Glass Based on Grey Relational Analysis |
title_full_unstemmed | Optimization of Shear-Thickening Polishing Parameters for Optical Glass Based on Grey Relational Analysis |
title_short | Optimization of Shear-Thickening Polishing Parameters for Optical Glass Based on Grey Relational Analysis |
title_sort | optimization of shear thickening polishing parameters for optical glass based on grey relational analysis |
topic | optical glass shear-thickening polishing orthogonal experiments grey relational analysis parameter optimization |
url | https://www.mdpi.com/2075-1702/13/1/40 |
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