Abstract
Abstract
When reporting surface quality, the roughest surface is a reference for the measurements. In LPBF due to recoil pressure and scan movement, asymmetric surface is shaped, and surface roughness has different values in different measurement orientations. In this research, the influence of the laser powder bed fusion (LPBF) process parameters on surface tension and roughness of Ti-6AI-4 V parts in three orientations are investigated. To improve the mechanical properties, heat treatment was carried out and added to the designed matrix to generate a comprehensive data set. Taguchi design of experiment was employed to print 25 samples with five process parameters and post-processing. The effect and interaction of the parameters on the formation of surface profile comprising tension, morphology and roughness in various directions have been analysed. The main contribution of this paper is developing a model to approximate the melting pool temperature and surface tension based on the process parameters. Other contributions are an analysis of process parameters to determine the formation and variation of surface tension and roughness and explain the governing mechanisms through rheological phenomena. Results showed that the main driving factors in the variation of surface tension and formation of the surface profile are thermophysical properties of the feedstock, rheology and the temperature of the melting pool. Also, the results showed that while the value of surface tension is the same for each test case, morphology and the value of roughness are different when analysing the surface in perpendicular, parallel and angled directions to laser movement.
Publisher
Springer Science and Business Media LLC
Subject
Industrial and Manufacturing Engineering,Computer Science Applications,Mechanical Engineering,Software,Control and Systems Engineering
Reference45 articles.
1. Nikam SH, Jain NK, Sawant MS (2020) Optimization of parameters of micro-plasma transferred arc additive manufacturing process using real coded genetic algorithm. Int J Adv Manuf Technol 106(3-4):1239–1252
2. Gibson I et al (2020) Additive manufacturing technologies, Third edn. Springer, Berlin
3. Ning J, Praniewicz M, Wang W, Dobbs JR, Liang SY (2020) Analytical modeling of part distortion in metal additive manufacturing. Int J Adv Manuf Technol 107(1):49–57
4. Mahdavi M, et al. (2020) Prediction of the deformation behavior of a selective laser-melted Ti-6Al-4V alloy as a function of process parameters. Int J Adv Manuf Technol. 1-8
5. Delfs P, Tows M, Schmid HJ (2016) Optimized build orientation of additive manufactured parts for improved surface quality and build time. Addit Manuf 12:314–320
Cited by
32 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献