| About this Abstract |
| Meeting |
MS&T23: Materials Science & Technology
|
| Symposium
|
Additive Manufacturing of Titanium-based Materials: Processing, Microstructure and Material Properties
|
| Presentation Title |
Correlating Laser Based Powder Bed Processing Conditions to the Fatigue Behavior of Additively Manufactured Ti-6Al-4V with As-Built Surfaces |
| Author(s) |
Jayme S. Keist, Scott Tokarz, Edward Reutzel, Vernon Cole, Debasis Sengupta |
| On-Site Speaker (Planned) |
Jayme S. Keist |
| Abstract Scope |
The fatigue of additively manufactured (AM) Ti-6Al-4V components varies widely depending on the surface condition. Although AM within a powder bed fusion (PBF) process allows for greater design freedom, the presence of as-built surfaces makes components prone to premature failure. Therefore, machining is usually employed to help improve the fatigue performance. Machining all surfaces, however, may be unrealistic for components with complicated geometries and with internal features. Instead, optimizing the PBF processing conditions can help improve the resulting fatigue performance of components with as-built surfaces. In this research, the impact of processing conditions such as layer thickness, build angle, and contour scanning strategies were investigated on the resulting roughness and high cycle fatigue performance. In addition, machine learning helped target critical processing parameters and revealed build design considerations that could be optimized to assure improved fatigue performance for components with as-built surfaces. |