Additive Manufacturing Performance Prediction from Print Measurements
Abstract
The proposed work will show the proof of concept of nondestructive testing (NDT) method for polymer and polymer composite 3D printing that will enable swift and accurate validation of 3D printed part geometry and will predict resultant mechanical properties and load capacity. NDT will be performed for the Fused Filament Fabrication (FFF) 3D printed part to detect delamination or cohesion bonds. Printing process data and temperature profile data will be collected during each layer printed. The data will then be correlated with the resultant 3D printed part geometry and mechanical strength using machine learning. In addition, if flaws are found by the thermal data in the newly printed layer, the printer may self-correct.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 12, 2025
- Source ID
- N001742310012
Entities
People
- Peter Lucon
Organizations
- Montana Technological University
- United States Navy