About this Abstract |
Meeting |
MS&T22: Materials Science & Technology
|
Symposium
|
2022 Undergraduate Student Poster Contest
|
Presentation Title |
Effects of Part Geometry and Toolpath Sequencing on Melt Pool Temperatures for Closed-loop Process Control in Laser Powder Bed Fusion |
Author(s) |
Ryan Zhou, Conor Porter, Dominik Kozjek, Jian Cao |
On-Site Speaker (Planned) |
Ryan Zhou |
Abstract Scope |
Melt pool temperature variation in metal laser powder bed fusion processes directly impact the quality and fidelity of builds. Both hot and cold spots are responsible for undesirable microstructural properties such as keyhole or lack-of-fusion porosity, heterogenous grain sizing, and surface roughness. Closed-loop process control allows for the dynamic adjustment of laser power and laser scanning speed based on in-situ temperature measurements. However, many build features affect how an algorithm should adjust process parameters. Toolpath sequencing and part geometry effects are abundant and have a complex series of interactions. Layer thickness and surface areas, hatch patterning and orientation, high aspect-ratio geometries, build plate positioning, and overhanging material all contribute uniquely towards dynamic melt pool temperature predictions. Planck pyrometry-derived melt pool data presented in this work can quantify the importance and interactions between these build parameters, and eventually may be used to develop machine learning training data for closed-loop process control. |