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Proceedings Papers

Brief Paper: Multi-Task Brain-Inspired Learning for Interlinking Machining Dynamics With Parts Geometrical Deviations

Danny Hoang, Hanning Chen, Mohsen Imani, Ruimin Chen, Farhad Imani
Proc. ASME. MSEC2024, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality & Reliability, V002T05A012, June 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2024-125435
https://doi.org/10.1115/MSEC2024-125435
View Paper titled, Brief Paper: Multi-Task Brain-Inspired Learning for Interlinking Machining Dynamics With Parts Geometrical Deviations
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Topics: Brain, Computers, Dynamics (Mechanics), Machining, Manufacturing, Computer numerical control machine tools, Product quality, Chatter, Machine learning, Surface roughness
Proceedings Papers

Data Efficient Modeling for Prediction and Forecasting of WAAM Process Conditions

Austen Thien, Nicole Van Handel, Helen Hu, Kyle Saleeby, Christopher Saldana
Proc. ASME. MSEC2024, Volume 1: Additive Manufacturing; Advanced Materials Manufacturing; Biomanufacturing; Life Cycle Engineering, V001T01A017, June 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2024-124113
https://doi.org/10.1115/MSEC2024-124113
View Paper titled, Data Efficient Modeling for Prediction and Forecasting of WAAM Process Conditions
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Topics: Additive manufacturing, Modeling, Time series, Wire, Artificial neural networks, Density, Geometry, Resolution (Optics), Feedstock, Machine learning
Proceedings Papers

A Deep MLP-CNN Model Using Metadata to Predict Melt Pool Morphology in LPBF: Effect of Geometrical Factors

Ehsan Vaghefi, Seyedmehrab Hosseini, Elham Mirkoohi
Proc. ASME. MSEC2024, Volume 1: Additive Manufacturing; Advanced Materials Manufacturing; Biomanufacturing; Life Cycle Engineering, V001T01A026, June 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2024-124641
https://doi.org/10.1115/MSEC2024-124641
View Paper titled, A Deep MLP-CNN Model Using Metadata to Predict Melt Pool Morphology in LPBF: Effect of Geometrical Factors
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Topics: Convolutional neural networks, Multilayer perceptron
Proceedings Papers

Artificial Intelligence-Based Design of Process Parameters in Laser Powder Bed Fusion of Ti-6Al-4V for Desired Solidification Structure

Ehsan Vaghefi, Elham Mirkoohi
Proc. ASME. MSEC2023, Volume 1: Additive Manufacturing; Advanced Materials Manufacturing; Biomanufacturing; Life Cycle Engineering, V001T01A013, June 12–16, 2023
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2023-104463
https://doi.org/10.1115/MSEC2023-104463
View Paper titled, Artificial Intelligence-Based Design of Process Parameters in Laser Powder Bed Fusion of Ti-6Al-4V for Desired Solidification Structure
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Topics: Additive manufacturing, Design, Lasers, Machine learning, Solidification, Temperature, Temperature gradient, Errors, Finite element analysis, Finite element model
Proceedings Papers

Friction Torque and Leakage Based Data-Driven Approach for Rotary Seal Prognostics in Manufacturing Industry

Madhumitha Ramachandran, Zahed Siddique
Proc. ASME. MSEC2019, Volume 1: Additive Manufacturing; Manufacturing Equipment and Systems; Bio and Sustainable Manufacturing, V001T02A028, June 10–14, 2019
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2019-2819
https://doi.org/10.1115/MSEC2019-2819
View Paper titled, Friction Torque and Leakage Based Data-Driven Approach for Rotary Seal Prognostics in Manufacturing Industry
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Topics: Friction, Leakage, Manufacturing industry, Multilayer perceptron, Production equipment, Torque
Proceedings Papers

Feature-Based Tool Condition Monitoring in a Gear Shaving Application

A. J. Brzezinski, Y. Wang, D. K. Choi, X. Qiao, J. Ni
Proc. ASME. MSEC2008, ASME 2008 International Manufacturing Science and Engineering Conference, Volume 2, 65-74, October 7–10, 2008
Publisher: American Society of Mechanical Engineers
Paper No: MSEC_ICM&P2008-72297
https://doi.org/10.1115/MSEC_ICMP2008-72297
View Paper titled, Feature-Based Tool Condition Monitoring in a Gear Shaving Application
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Topics: Condition monitoring, Gears, Wear, Artificial neural networks, Cutting tools, Data collection, Dimensions, Feature extraction, Machinery, Multilayer perceptron