About this Abstract |
Meeting |
Advances in Welding and Additive Manufacturing Research 2022
|
Symposium
|
Advances in Welding and Additive Manufacturing Research 2022
|
Presentation Title |
Process Monitoring for Functionally Graded Material Development using Laser Directed Energy Deposition |
Author(s) |
Lee Kerwin, Alex Kitt, Luke Mohr, Anindya Bhaduri, Chen Shen, Siyeong Ju, Hyeyun Song, Shenyan Huang, Arushi Dhakad, Sathyanarayanan Raghavan, Lang Yuan, Changjie Sun |
On-Site Speaker (Planned) |
Lee Kerwin |
Abstract Scope |
This work is developing the process to successfully create FGMs with low gamma-prime and high gamma-prime nickel-based superalloys. The focus of this program is the implementation of process monitoring and machine learning to identify the process inputs to produce FGM samples with no cracks and >99% material density. In-situ monitoring using melt-pool video, thermal gradient and melt-pool temperature monitoring was used to analyze and validate process conditions for optimal build parameters. Through iterative parameter development and transfer learning, the team achieved thick-wall development samples of Inconel 718 and Rene 41 that were crack free. The program is progressing with increasingly complex geometries and will result in an FGM-deposited test article representing a full-scale hot and harsh gas-path portion of a gas turbine engine being built. This presentation will describe how homogenous mixtures of dissimilar materials were calibrated and deposited in a controlled manner to create crack free test samples. Further, it will describe how in-process monitoring was implemented and utilized to reduce the amount of development time needed to accomplish crack-free multi-material build samples. |
Proceedings Inclusion? |
Undecided |