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Meeting 2023 TMS Annual Meeting & Exhibition
Symposium Quantifying Microstructure Heterogeneity for Qualification of Additively Manufactured Materials
Presentation Title 3D Computer Vision and Machine Learning for Porosity Analysis in Additive Manufacturing
Author(s) Daniel Diaz, Yuheng Nie, Anthony Rollett, Elizabeth Holm
On-Site Speaker (Planned) Daniel Diaz
Abstract Scope Additive manufacturing (AM) is a promising novel technology that is revolutionizing the way we manufacture products, but many properties are limited by porosity produced during processing. In order to better understand the relationship between pore morphologies and properties, it is necessary to accurately identify the characteristic classes of pores observed. To this end we leverage the tools of 3D computer vision and convolutional neural networks to examine the pore morphologies present in datasets collected using X-ray computed tomography (CT). A transfer learning approach is utilized where 3D versions of EfficientNet are initialized with weights that have been trained on ImageNet and converted to a 3D format. Segmented CT image stacks are fed into this pretrained network, and the results are used to divide the pores into clusters that aid in identifying the various morphologies. This has the potential to become a valuable tool for automating the characterization of AM products.
Proceedings Inclusion? Planned:
Keywords Additive Manufacturing, Machine Learning, Characterization

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

3D Computer Vision and Machine Learning for Porosity Analysis in Additive Manufacturing
A study of microstructural and mechanical properties of 14YWT Oxide Dispersion Strengthened steel fabricated using Laser Powder Bed Fusion Additive Manufacturing from Gas Atomized Reaction Synthesis feedstock
Additive Manufacturing beyond the Gaussian Beam: Insights from Microstructure-based Modeling Studies
Build Geometry and Parameter Influence on Alloy 718 Microstructure, Properties and Spatial Variation in Additive Manufacturing
Characterization of Titanium Additions in Selectively Laser Melted High-Strength Aluminum Alloy by Correlative X-Ray and Electron Microscopy
Control of Residual Stress and Distortion in Metal Additive Manufacturing via Inverse Mapping of Textures
Correlative Modeling of Laser Powder Bed Fusion Surface Characteristics to Internal Defects
Effects of Laser Process Parameters on Denudation Zone Width in Laser Powder Bed Fusion Additive Manufacturing
Effects of Processing Conditions and Build Geometry on Microstructure Development in Laser Powder Bed Fusion and Wire Arc Additively Manufactured 316L
Heterogeneous Microstructure and Location-Specific Mechanical Performance of Ti-6Al-4V Parts Made by Laser Directed Energy Deposition
In situ monitoring of recrystallization during Laser Powder Bed Fusion of 316L stainless steel by means of Synchrotron X-ray diffraction
Intentionally Seeding Pores in Laser Powder Bed Fusion IN718: Microstructure, Defects, and Fatigue
Investigating the potential of indentation-based methods for microstructure heterogeneity assessment during manufacturing
Large-scale image analysis of melt pools in complex additively manufactured artifacts
Location specific characterization of additively manufactured stainless steel to inform build data analytics
Long-term Process Stability in Laser Powder Bed Fusion
Microstructural and Mechanical Validation of Thin-Walled Additively Manufactured Inconel 625
Microstructure and mechanical property variations in commercially produced laser powder bed fusion 316L stainless steel
Microstructure Evolution According to Heat Treatment Design of Alloy 625 Produced by Selective Laser Melting
NASA’s approach on the evaluations of “material engineering equivalence” methodology in achieving and sustaining efficient qualification and certification of AM materials and parts
Opportunities & Challenges with Laser Powder Bed Fusion for Automotive Applications: Steel and Aluminum Alloys
Optimizing Creep Performance of Haynes 282 Printed via Laser Powder Bed Fusion through Microstructure Control
Predicting Crystallographic Texture in Laser Powder Bed Fusion via a Machine Learning Approach
Quantification of Microstructural Heterogeneities in Additively Manufactured and Heat-Treated Haynes 282
Quantitative Analysis of Computed Tomography Characterization of Porosity in AM Ti64 using Serial Sectioning Ground Truth
Quantitative analysis of low concentration elements at the nanoscale in additively manufactured alloys
Strategizing with hot isostatic pressing treatments to increase productivity during post-processing of laser-melted Inconel 718 parts
Strong impact of minor elements on the microstructural evolution of an additively manufactured Inconel 625 alloy
Synchrotron-based X-ray microtomography characterization of solidification cracks in additively manufactured IN738LC alloy
The Effect of Beam Shaping Strategies on Additively Manufactured Microstructures
The impact of volumetric energy density on mechanical properties of additively manufactured 718 Ni alloy
Towards Validation of Thermo-Mechanical Finite Element Modeling of the Additive Manufacturing Solidification Process
Use of Profilometry-based Indentation Plastometry (PIP) to Study Inhomogeneities in Additively Manufactured Components
X-ray Diffraction Peak Estimation Using In-Situ Melt-pool Sensors

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