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Mojtaba Khanzadeh
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Proceedings Papers

Anomaly Detection of Laser-Based Metal Additive Manufacturing Using Neural-Variational Auto-Encoder

Sean Rescsanski, Aref Yadollahi, Mojtaba Khanzadeh, Farhad Imani
Proc. ASME. MSEC2023, Volume 1: Additive Manufacturing; Advanced Materials Manufacturing; Biomanufacturing; Life Cycle Engineering, V001T01A026, June 12–16, 2023
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2023-105156
https://doi.org/10.1115/MSEC2023-105156
View Paper titled, Anomaly Detection of Laser-Based Metal Additive Manufacturing Using Neural-Variational Auto-Encoder
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Topics: Additive manufacturing, Lasers, Metals
Proceedings Papers

Image-Guided Multi-Response Modeling and Characterization of Design Defects in Metal Additive Manufacturing

Farhad Imani, Mojtaba Khanzadeh
Proc. ASME. IMECE2021, Volume 2B: Advanced Manufacturing, V02BT02A046, November 1–5, 2021
Publisher: American Society of Mechanical Engineers
Paper No: IMECE2021-71966
https://doi.org/10.1115/IMECE2021-71966
View Paper titled, Image-Guided Multi-Response Modeling and Characterization of Design Defects in Metal Additive Manufacturing
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Topics: Additive manufacturing, Design, Metals, Modeling
Journal Articles

Fast Prediction of Thermal Data Stream for Direct Laser Deposition Processes Using Network-Based Tensor Regression

Mojtaba Khanzadeh, Matthew Dantin, Wenmeng Tian, Matthew W. Priddy, Haley Doude, Linkan Bian
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Research Papers
J. Manuf. Sci. Eng. April 2022, 144(4): 041004.
Paper No: MANU-20-1523
https://doi.org/10.1115/1.4052207
Published Online: September 23, 2021
View Article titled, Fast Prediction of Thermal Data Stream for Direct Laser Deposition Processes Using Network-Based Tensor Regression
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Topics: Modeling, Physics, Tensors, Simulation
Journal Articles

Quantifying Geometric Accuracy With Unsupervised Machine Learning: Using Self-Organizing Map on Fused Filament Fabrication Additive Manufacturing Parts

Mojtaba Khanzadeh, Prahalada Rao, Ruholla Jafari-Marandi, Brian K. Smith, Mark A. Tschopp, Linkan Bian
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Research-Article
J. Manuf. Sci. Eng. March 2018, 140(3): 031011.
Paper No: MANU-17-1366
https://doi.org/10.1115/1.4038598
Published Online: December 21, 2017
View Article titled, Quantifying Geometric Accuracy With Unsupervised Machine Learning: Using Self-Organizing Map on Fused Filament Fabrication Additive Manufacturing Parts
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Topics: Additive manufacturing, Lasers, Machine learning, Manufacturing, Modeling, Self-organization, Shapes, Temperature
Proceedings Papers

A Methodology for Predicting Porosity From Thermal Imaging of Melt Pools in Additive Manufacturing Thin Wall Sections

Mojtaba Khanzadeh, Sudipta Chowdhury, Linkan Bian, Mark A. Tschopp
Proc. ASME. MSEC2017, Volume 2: Additive Manufacturing; Materials, V002T01A044, June 4–8, 2017
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2017-2909
https://doi.org/10.1115/MSEC2017-2909
View Paper titled, A Methodology for Predicting Porosity From Thermal Imaging of Melt Pools in Additive Manufacturing Thin Wall Sections
Open the PDF for A Methodology for Predicting Porosity From Thermal Imaging of Melt Pools in Additive Manufacturing Thin Wall Sections in another window
Topics: Additive manufacturing, Imaging, Porosity, Thin wall structures, Lasers, Mechanical properties, Self-organization, Temperature distribution, X-rays