About this Abstract |
Meeting |
MS&T24: Materials Science & Technology
|
Symposium
|
Additive Manufacturing Modeling, Simulation, and Machine Learning: Microstructure, Mechanics, and Process
|
Presentation Title |
CAD to Part Methodology for Process Structure and Performance (PSPP) |
Author(s) |
Ross Gregoriev, Kyle Rosenow |
On-Site Speaker (Planned) |
Ross Gregoriev |
Abstract Scope |
The ability for additive manufacturing to create complex geometries is a double edge sword. New geometry freedom enhances part value and performance, but can complicate part material conditions. Increases in part size and complexity has stretched NDT methods to their limits. As a result, simulation enhanced CAD to Part (CAD2Part) processes drive more confidence into the quality of a part.
This work describes an integrated CAD2Part workflow approach that connects process parameters, in-situ process monitoring, and Computational Materials Engineering (CME) to advance the material quality assurance for Additive Manufacturing (AM) components. The workflow utilizes calibration backed, multiscale simulation results to propose parameter changes a-priori. The pre-build analysis aims to mitigate thermal effects that impact weld consistency and quality. Validation of improved quality and consistency is performed using metallography and an in-situ thermal imager to measure changes to melt pool characteristics in a complex geometry.
Copyright 2024 Lockheed Martin Corporation |