Research experimental on surface integrity and parameters optimization of micro-milling dual-phase titanium alloy

Abstract As the application of dual-phase polycrystalline materials in micro-components expands, the surface integrity evaluation criteria developed for macro-scale machining are become insufficient. To investigate the effects of cutting parameters on surface integrity at the micro-scale, a typical dual-phase titanium alloy was selected as the subject for micro-milling. First, a physical experimental platform for micro-milling was established. Subsequently, a single-factor experimental method was employed to analyze the effects of cutting parameters on the micro-morphology, surface roughness, and micro-hardness of the processed dual-phase titanium alloy. Following this, orthogonal experimental range analysis and response surface variance analysis were conducted to evaluate the significance of cutting parameters on the target factors. Finally, cutting parameters were optimized using the signal-to-noise ratio method and response surface methodology, followed by physical experimental validation. Results reveal that feed per tooth significantly influences surface roughness, while cutting depth least. In contrast, spindle speed is the primary factor affecting micro-hardness, with feed per tooth having minimal effect. Optimal parameters minimize both surface roughness and micro-hardness, with experimental and theoretical values differing by no more than 5%. The findings provide both theoretical and experimental support for the surface integrity and parameters optimization of dual-phase alloys in micro-machining.

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Publication Details

Journal
Surface Topography Metrology and Properties
Published
2025-02-12
DOI
https://doi.org/10.1088/2051-672x/adaf48
Citations
3
Primary Topic
Advanced machining processes and optimization
Type
article
Field-Weighted Citation Impact
2.14

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article

Research experimental on surface integrity and parameters optimization of micro-milling dual-phase titanium alloy

Weiliang He, Yan Cao, Sergey Gorbachev, Victor Kuzin et al.
3 citations
Surface Topography Metrology and Properties
Advanced machining processes and optimization
2.14
article

Research experimental on surface integrity and parameters optimization of micro-milling dual-phase titanium alloy

Weiliang He, Yan Cao, Sergey Gorbachev, Victor Kuzin, HaiYue Zhao, Jiang Du
article en
3 citations

Abstract

Abstract As the application of dual-phase polycrystalline materials in micro-components expands, the surface integrity evaluation criteria developed for macro-scale machining are become insufficient. To investigate the effects of cutting parameters on surface integrity at the micro-scale, a typical dual-phase titanium alloy was selected as the subject for micro-milling. First, a physical experimental platform for micro-milling was established. Subsequently, a single-factor experimental method was employed to analyze the effects of cutting parameters on the micro-morphology, surface roughness, and micro-hardness of the processed dual-phase titanium alloy. Following this, orthogonal experimental range analysis and response surface variance analysis were conducted to evaluate the significance of cutting parameters on the target factors. Finally, cutting parameters were optimized using the signal-to-noise ratio method and response surface methodology, followed by physical experimental validation. Results reveal that feed per tooth significantly influences surface roughness, while cutting depth least. In contrast, spindle speed is the primary factor affecting micro-hardness, with feed per tooth having minimal effect. Optimal parameters minimize both surface roughness and micro-hardness, with experimental and theoretical values differing by no more than 5%. The findings provide both theoretical and experimental support for the surface integrity and parameters optimization of dual-phase alloys in micro-machining.

Surface Topography Metrology and PropertiesVol. 13(1)
Chongqing University (CN), Russian Engineering Academy (RU), Xi'an Technological University (CN), Shaanxi Polytechnic University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 15%
Advanced machining processes and optimization
2.14
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