Titanium Alloy Turning Machining Model and Quality Analysis Based on Finite Element Analysis

Workpiece fabrication of titanium alloy is widely used in several high-end fields. In this study, finite element analysis of titanium alloy turning process is carried out and the turning process is modeled by using material properties and intrinsic equations. Then the power transmission of centerless lathe is controlled in the machining process, so as to obtain the performance calculation of different process parameters on cutting force, chips, and residual stress. The analysis of the simulation and experimental data yielded that when the tool travel speed was 1 m/min, the radial force increased to a maximum value of 150N. When the depth of cut was 0.3mm, the radial force was 151N and then increased to 200N. In the comparison of the simulation results, it was concluded that the depth of cut was 0.3mm, the minimum error value was 7.43%. In the quality analysis, the optimum parameters for travel speed and depth of cut were 1.0 m/min and 0.2mm respectively. When the spindle speed was 480 r/min, the roughness of the machined surface of titanium alloy was closer to the simulation results, and the lowest difference was 0.1 μm. Therefore, the finite element machining model of titanium alloy turning proposed by the study could effectively improve the machining quality and accuracy, and it has superiority. In the future machining and parts manufacturing, it can improve the processing efficiency and promote the optimization of titanium alloy material properties.

Authors

Publication Details

Journal
MANUFACTURING TECHNOLOGY
Published
2025-05-23
DOI
https://doi.org/10.21062/mft.2025.036
Citations
3
Primary Topic
Advanced machining processes and optimization
Type
article
Field-Weighted Citation Impact
2.14
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Titanium Alloy Turning Machining Model and Quality Analysis Based on Finite Element Analysis

H.Q. Yin, Zhen-Hua Wang
3 citations
MANUFACTURING TECHNOLOGY
Advanced machining processes and optimization
2.14
article

Titanium Alloy Turning Machining Model and Quality Analysis Based on Finite Element Analysis

H.Q. Yin, Zhen-Hua Wang
article en
3 citations

Abstract

Workpiece fabrication of titanium alloy is widely used in several high-end fields. In this study, finite element analysis of titanium alloy turning process is carried out and the turning process is modeled by using material properties and intrinsic equations. Then the power transmission of centerless lathe is controlled in the machining process, so as to obtain the performance calculation of different process parameters on cutting force, chips, and residual stress. The analysis of the simulation and experimental data yielded that when the tool travel speed was 1 m/min, the radial force increased to a maximum value of 150N. When the depth of cut was 0.3mm, the radial force was 151N and then increased to 200N. In the comparison of the simulation results, it was concluded that the depth of cut was 0.3mm, the minimum error value was 7.43%. In the quality analysis, the optimum parameters for travel speed and depth of cut were 1.0 m/min and 0.2mm respectively. When the spindle speed was 480 r/min, the roughness of the machined surface of titanium alloy was closer to the simulation results, and the lowest difference was 0.1 μm. Therefore, the finite element machining model of titanium alloy turning proposed by the study could effectively improve the machining quality and accuracy, and it has superiority. In the future machining and parts manufacturing, it can improve the processing efficiency and promote the optimization of titanium alloy material properties.

MANUFACTURING TECHNOLOGYVol. 25(3)
Openalex Percentile: Top 14%
Advanced machining processes and optimization
2.14
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.