About this Abstract |
Meeting |
2024 TMS Annual Meeting & Exhibition
|
Symposium
|
Additive Manufacturing Modeling, Simulation and Machine Learning
|
Presentation Title |
F-18: Efficient Process Parameter Optimization for Titanium Alloys in Additive Manufacturing |
Author(s) |
Thorsten Hermann Becker, Sabrina Rudolph |
On-Site Speaker (Planned) |
Thorsten Hermann Becker |
Abstract Scope |
Process parameter optimization for the development of new alloys in additive manufacturing often involves extensive experimental studies, typically focusing on either single-track investigations or large parameter variation matrices. This research proposes an alternative approach to characterize the processing windows of titanium alloys produced using laser powder bed fusion (LPBF). The feasibility of implementing a D-optimal design approach is explored to significantly reduce the number of samples required for the process parameter optimization. In this study, laser power, scan speed, and hatch distance are varied within an optimized design space to investigate their impact on the porosity and microstructural features of five titanium alloys, namely Ti-6A-4V, Ti-5Al-5Mo-5V-3Cr, Ti-15Mo-2.7Nb-3Al-0.2Si, Ti-6Al-2Sn-4Zr-6Mo, and Ti-6.5Al-3.5Mo-1.5Zr-0.3Si. The study demonstrates how the iterative search in the D-optimal design approach offers the opportunity to minimize the experimental program and efficiently identify optimal processing windows. Trends between the alloy composition, density, microstructure, and process window are highlighted. |
Proceedings Inclusion? |
Planned: |
Keywords |
Additive Manufacturing, Titanium, Modeling and Simulation |