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Proceedings Papers

Support-Structure Decision in 3D Printing With Unsupervised Computer Vision

Shenghan Guo, Hasnaa Ouidadi, Boyang Xu
Proc. ASME. MSEC2024, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality & Reliability, V002T07A001, June 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2024-124409
https://doi.org/10.1115/MSEC2024-124409
View Paper titled, Support-Structure Decision in 3D Printing With Unsupervised Computer Vision
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Topics: Additive manufacturing, Computer vision, Computer-aided design
Proceedings Papers

A Physical Comprehensive Model for Studying Temperature Evolution in FDM 3D Printing

Haofan Sun, Magnas Joseph Albert, Srikar Anudeep Remani, Shenghan Guo, Qiong Nian
Proc. ASME. MSEC2024, Volume 1: Additive Manufacturing; Advanced Materials Manufacturing; Biomanufacturing; Life Cycle Engineering, V001T01A051, June 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2024-125563
https://doi.org/10.1115/MSEC2024-125563
View Paper titled, A Physical Comprehensive Model for Studying Temperature Evolution in FDM 3D Printing
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Topics: Additive manufacturing, Finite element methods, Heat transfer, Temperature
Journal Articles

Three-Dimensional X-Ray Computed Tomography Image Segmentation and Point Cloud Reconstruction for Internal Defect Identification in Laser Powder Bed Fused Parts

Boyang Xu, Hasnaa Ouidadi, Nicole Van Handel, Shenghan Guo
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Research Papers
J. Manuf. Sci. Eng. September 2024, 146(9): 091002.
Paper No: MANU-23-1666
https://doi.org/10.1115/1.4065179
Published Online: June 3, 2024
View Article titled, Three-Dimensional X-Ray Computed Tomography Image Segmentation and Point Cloud Reconstruction for Internal Defect Identification in Laser Powder Bed Fused Parts
Open the PDF for Three-Dimensional X-Ray Computed Tomography Image Segmentation and Point Cloud Reconstruction for Internal Defect Identification in Laser Powder Bed Fused Parts in another window
Topics: Image segmentation, Shapes, Computerized tomography, Lasers
Proceedings Papers

Defect Segmentation From X-Ray Computed Tomography of Laser Powder Bed Fusion Parts: A Comparative Study Among Machine Learning, Deep Learning, and Statistical Image Thresholding Methods

Hasnaa Ouidadi, Boyang Xu, Shenghan Guo
Proc. ASME. MSEC2023, Volume 1: Additive Manufacturing; Advanced Materials Manufacturing; Biomanufacturing; Life Cycle Engineering, V001T01A012, June 12–16, 2023
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2023-104387
https://doi.org/10.1115/MSEC2023-104387
View Paper titled, Defect Segmentation From X-Ray Computed Tomography of Laser Powder Bed Fusion Parts: A Comparative Study Among Machine Learning, Deep Learning, and Statistical Image Thresholding Methods
Open the PDF for Defect Segmentation From X-Ray Computed Tomography of Laser Powder Bed Fusion Parts: A Comparative Study Among Machine Learning, Deep Learning, and Statistical Image Thresholding Methods in another window
Topics: Computerized tomography, Image segmentation, Lasers, Machine learning
Proceedings Papers

Process Signature Characterization and Anomaly Detection With Personalized PCA in Laser-Based Metal Additive Manufacturing

Naichen Shi, Raed Al Kontar, Shenghan Guo
Proc. ASME. MSEC2023, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T09A007, June 12–16, 2023
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2023-105080
https://doi.org/10.1115/MSEC2023-105080
View Paper titled, Process Signature Characterization and Anomaly Detection With Personalized PCA in Laser-Based Metal Additive Manufacturing
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Topics: Additive manufacturing, Lasers, Metals, Principal component analysis
Proceedings Papers

Learning the Temporal Effect in Infrared Thermal Videos With Long Short-Term Memory for Quality Prediction in Resistance Spot Welding

Shenghan Guo, Dali Wang, Jian Chen, Zhili Feng, Weihong “Grace” Guo
Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T05A035, June 27–July 1, 2022
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2022-85422
https://doi.org/10.1115/MSEC2022-85422
View Paper titled, Learning the Temporal Effect in Infrared Thermal Videos With Long Short-Term Memory for Quality Prediction in Resistance Spot Welding
Open the PDF for Learning the Temporal Effect in Infrared Thermal Videos With Long Short-Term Memory for Quality Prediction in Resistance Spot Welding in another window
Topics: Welding
Proceedings Papers

Image-Based Fractographic Pattern Recognition With Cluster Analysis

Shenghan Guo, Paul Paradise, Nicole Van Handel, Dhruv Bhate
Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T05A008, June 27–July 1, 2022
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2022-82773
https://doi.org/10.1115/MSEC2022-82773
View Paper titled, Image-Based Fractographic Pattern Recognition With Cluster Analysis
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Topics: Fractography, Fracture (Materials), Pattern recognition, Additive manufacturing, Algorithms, Artificial neural networks, Decision making, High cycle fatigue, Inspection, Scanning electron microscopy
Journal Articles

Predicting Nugget Size of Resistance Spot Welds Using Infrared Thermal Videos With Image Segmentation and Convolutional Neural Network

Shenghan Guo, Dali Wang, Jian Chen, Zhili Feng, Weihong “Grace” Guo
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Research Papers
J. Manuf. Sci. Eng. February 2022, 144(2): 021009.
Paper No: MANU-21-1309
https://doi.org/10.1115/1.4051829
Published Online: August 5, 2021
View Article titled, Predicting Nugget Size of Resistance Spot Welds Using Infrared Thermal Videos With Image Segmentation and Convolutional Neural Network
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Topics: Artificial neural networks, Image segmentation, Nondestructive evaluation, Welding, Construction, Joining, Welded joints, Regression models
Proceedings Papers

Predicting Nugget Size of Resistance Spot Welds Using Infrared Thermal Videos With Image Segmentation and Convolutional Neural Network

Shenghan Guo, Dali Wang, Jian Chen, Zhili Feng, Weihong “Grace” Guo
Proc. ASME. MSEC2021, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T06A011, June 21–25, 2021
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2021-61775
https://doi.org/10.1115/MSEC2021-61775
View Paper titled, Predicting Nugget Size of Resistance Spot Welds Using Infrared Thermal Videos With Image Segmentation and Convolutional Neural Network
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Topics: Artificial neural networks, Image segmentation, Nondestructive evaluation, Welded joints, Welding
Proceedings Papers

Deep Learning-Based Data Fusion Method for In-Situ Porosity Detection in Laser-Based Additive Manufacturing

Qi Tian, Shenghan Guo, Weihong Guo, Linkan Bian
Proc. ASME. MSEC2020, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A032, September 3, 2020
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2020-8468
https://doi.org/10.1115/MSEC2020-8468
View Paper titled, Deep Learning-Based Data Fusion Method for In-Situ Porosity Detection in Laser-Based Additive Manufacturing
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Topics: Additive manufacturing, Data fusion, Lasers, Porosity
Journal Articles

Deep Learning-Based Data Fusion Method for In Situ Porosity Detection in Laser-Based Additive Manufacturing

Qi Tian, Shenghan Guo, Erika Melder, Linkan Bian, Weihong “Grace” Guo
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Research Papers
J. Manuf. Sci. Eng. April 2021, 143(4): 041011.
Paper No: MANU-20-1337
https://doi.org/10.1115/1.4048957
Published Online: December 17, 2020
View Article titled, Deep Learning-Based Data Fusion Method for In Situ Porosity Detection in Laser-Based Additive Manufacturing
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Topics: Data fusion, Porosity, Pyrometers, Lasers, Additive manufacturing
Journal Articles

Manufacturing Process Monitoring With Nonparametric Change-Point Detection in Automotive Industry

Shenghan Guo, Weihong (Grace) Guo, Amir Abolhassani, Rajeev Kalamdani, Saumuy Puchala, Annette Januszczak, Chandra Jalluri
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Research-Article
J. Manuf. Sci. Eng. July 2019, 141(7): 071013.
Paper No: MANU-18-1506
https://doi.org/10.1115/1.4043732
Published Online: May 28, 2019
View Article titled, Manufacturing Process Monitoring With Nonparametric Change-Point Detection in Automotive Industry
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Topics: Image segmentation, Maintenance, Manufacturing, Decision making, Automotive industry