Manufacturing Technology 2024, 24(4):652-667 | DOI: 10.21062/mft.2024.064

Study on Multi-Objective Optimization of Milling Process of Powder Metallurgy Titanium Aluminum Alloys

Wenbing Tian ORCID...^1,2, Wenhu Wang^1,2, Yuanbin Wang ORCID...^1,2, Shengguo Zhang ORCID...^1,2

¹ Key Laboratory of High Performance Manufacturing for Aero Engine, Ministry of Industry and Information Technology, School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an 710072, Shaanxi, PR China

² Engineering Research Center of Advanced Manufacturing Technology for Aero Engine, Ministry of Education, School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, Shaanxi, PR China

Currently, there is a demand in the aerospace industry for a more effective and non-invasive milling technique for powder metallurgy γ-TiAl alloy. The primary objective of this research is to examine the surface milling process of a γ-TiAl alloy generated by powder metallurgy. The primary objective of this study is to examine the impact of process parameters on the surface roughness and cutting force of the alloy, with the aim of optimizing both surface roughness and cutting force. The response surface method was implemented to examine the milling process, and the NSGA II algorithm was employed to optimise surface roughness, cutting force, and material removal rate. The findings indicate that the cutting depth exerts a significant impact on both the surface morphology and surface roughness. The available data indicates a clear correlation between the depth of cutting and the rate of feed, as well as the resulting assessment of surface roughness. Nevertheless, the first rise in spindle speed is associated with a subsequent increase in surface roughness, followed by a subsequent drop of a lesser magnitude. A minimal threshold for surface roughness has been established at 0.203μm. The spindle speed exerts the primary impact on the cutting force. There exists a positive link between the cutting force value and both the cutting depth and feed speed, as the cutting force value has a positive correlation with the incremental changes in these variables. Nevertheless, the relationship between cutting force and the observed trend is non-linear, exhibiting an initial decrease followed by a rise when cutting force is augmented. The minimal cutting force necessary was quantified as 112.3 N. Subsequently, a regression analysis was employed to develop a correlation model between surface roughness and cutting force. and machining parameters. The confirmation of the coefficients' validity in the model was achieved via the utilisation of analysis of variance (ANOVA) and residual analysis. The main goal of developing a machining parameter optimisation model is to limit surface roughness and cutting force, thereby improving operational efficiency. The NSGA-II method is utilised to tackle the problem of multi-objective optimisation, leading to the attainment of the optimal parameter solution. The purpose of the verification test is to evaluate the precision of the forecasts generated by the optimised model. The work holds importance in its analysis and juxtaposition of diverse processing factors, alongside the use of multi-objective optimization methodologies.

Keywords: Powder metallurgyγ-TiAl alloy, Cutting force, Surface roughness, Multi-objective optimization

Grants and funding:

This article is supported by the project "Research on TiAl-4522XD Alloys Low Pressure Turbine Working Blade Powder Hot Isostatic Pressing Near Net Forming Technology" hosted by China Aviation Industry Corporation, with project number ZZCX-2020-007

Received: December 31, 2023; Revised: April 28, 2024; Accepted: June 24, 2024; Prepublished online: July 9, 2024; Published: September 1, 2024  Show citation