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Proceedings Papers

An Active Machine Learning Approach for Spatial-Temporal Temperature Prediction of a Moving Heat Source

Mahtab Heydari, Bruce Tai
Proc. ASME. MSEC2024, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality & Reliability, V002T07A008, June 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2024-125289
https://doi.org/10.1115/MSEC2024-125289
View Paper titled, An Active Machine Learning Approach for Spatial-Temporal Temperature Prediction of a Moving Heat Source
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Topics: Heat, Machine learning, Temperature, Additive manufacturing, Artificial neural networks, Computer simulation, Laser cutting, Machining, Manufacturing, Trains
Proceedings Papers

Deep Learning-Based Recognition of Manufacturing Components Using Augmented Reality for Worker Training of Assembly Tasks

Sourabh Deshpande, Manish Raj Aryal, Sam Anand
Proc. ASME. MSEC2024, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality & Reliability, V002T07A007, June 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2024-125279
https://doi.org/10.1115/MSEC2024-125279
View Paper titled, Deep Learning-Based Recognition of Manufacturing Components Using Augmented Reality for Worker Training of Assembly Tasks
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Topics: Augmented reality, Deep learning, Manufacturing, Engines, Artificial neural networks, Computer-aided design, Computers, Additive manufacturing, Algorithms, Artificial intelligence
Proceedings Papers

A Deep Reinforcement Learning Approach for Production Scheduling in Computer Server Industry

Azzam Radman, Faisal Aqlan, Pratik Parikh, Md. Noor E. Alam
Proc. ASME. MSEC2024, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality & Reliability, V002T07A011, June 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2024-130310
https://doi.org/10.1115/MSEC2024-130310
View Paper titled, A Deep Reinforcement Learning Approach for Production Scheduling in Computer Server Industry
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Topics: Computers, Deep reinforcement learning
Proceedings Papers

Generating Optimized 3d Designs for Manufacturing Using a Guided Voxel Diffusion Model

Premith Kumar Chilukuri, Binyang Song, SungKu Kang, Ran Jin
Proc. ASME. MSEC2024, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality & Reliability, V002T07A006, June 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2024-125075
https://doi.org/10.1115/MSEC2024-125075
View Paper titled, Generating Optimized 3d Designs for Manufacturing Using a Guided Voxel Diffusion Model
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Topics: Design, Diffusion (Physics), Manufacturing, Shapes, Voxel
Proceedings Papers

Electrospinning Process Modeling: A Multi-Stage View

Christian Zuniga-Navarrete, Stalin Jamil Segura, Sabur Baidya, Christian Narváez-Muñoz, Juan Diego Toscano, Luis Javier Segura
Proc. ASME. MSEC2024, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality & Reliability, V002T07A005, June 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2024-125011
https://doi.org/10.1115/MSEC2024-125011
View Paper titled, Electrospinning Process Modeling: A Multi-Stage View
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Topics: Electrospinning, Modeling, Tensors, Trains
Proceedings Papers

Physics-Informed Loss Functions With Explainable AI to Predict Emission in Powder Bed Fusion

Ethan Regal, Vidita Gawade, Weihong Guo
Proc. ASME. MSEC2024, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality & Reliability, V002T07A010, June 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2024-125898
https://doi.org/10.1115/MSEC2024-125898
View Paper titled, Physics-Informed Loss Functions With Explainable AI to Predict Emission in Powder Bed Fusion
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Topics: Emissions, Physics, Printing, Artificial neural networks, Deep learning, Errors, Metals, Stability, Transparency
Proceedings Papers

Real-Time Print Tracking in Metal Additive Manufacturing Using Acoustic Emission Sensors and Vision Transformer Algorithms

Javid Akhavan, Ke Xu, Chaitanya Krishna Vallabh, Souran Manoochehri
Proc. ASME. MSEC2024, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality & Reliability, V002T07A009, June 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2024-125391
https://doi.org/10.1115/MSEC2024-125391
View Paper titled, Real-Time Print Tracking in Metal Additive Manufacturing Using Acoustic Emission Sensors and Vision Transformer Algorithms
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Topics: Acoustic emissions, Additive manufacturing, Algorithms, Lasers, Metals, Sensors
Proceedings Papers

Bridging Data Gaps: a Federated Learning Approach to Heat Emission Prediction in Laser Powder Bed Fusion

Rong Lei, Yuebin Guo, Weihong “Grace” Guo
Proc. ASME. MSEC2024, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality & Reliability, V002T07A004, June 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2024-124768
https://doi.org/10.1115/MSEC2024-124768
View Paper titled, Bridging Data Gaps: a Federated Learning Approach to Heat Emission Prediction in Laser Powder Bed Fusion
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Topics: Additive manufacturing, Emissions, Heat, Lasers
Proceedings Papers

A Task Allocation and Scheduling Framework to Facilitate Efficient Human-Robot Collaboration in High-Mix Assembly Applications

Jeon Ho Kang, Neel Dhanaraj, Omey M. Manyar, Siddhant Wadaskar, Satyandra K. Gupta
Proc. ASME. MSEC2024, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality & Reliability, V002T07A003, June 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2024-124764
https://doi.org/10.1115/MSEC2024-124764
View Paper titled, A Task Allocation and Scheduling Framework to Facilitate Efficient Human-Robot Collaboration in High-Mix Assembly Applications
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Topics: Human-robot collaboration, Manufacturing, Robots, Collaboration, Failure, Teams
Proceedings Papers

Efficient Cutting Tool Wear Segmentation Based on Segment Anything Model

Zongshuo Li, Ding Huo, Markus Meurer, Thomas Bergs
Proc. ASME. MSEC2024, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality & Reliability, V002T07A002, June 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2024-124455
https://doi.org/10.1115/MSEC2024-124455
View Paper titled, Efficient Cutting Tool Wear Segmentation Based on Segment Anything Model
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Topics: Cutting tools, Image segmentation, Wear
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

Full Stack Virtual Commissioning: Requirements Framework to Bridge Gaps in Current Virtual Commissioning Process

Jonathan B. Sim, Kavan N. Shah, Miguel Saez, Jeffrey Abell, Yanli Zhou, John Faris, Dawn M. Tilbury, Kira Barton
Proc. ASME. MSEC2023, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A016, June 12–16, 2023
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2023-106670
https://doi.org/10.1115/MSEC2023-106670
View Paper titled, Full Stack Virtual Commissioning: Requirements Framework to Bridge Gaps in Current Virtual Commissioning Process
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Topics: Bridges (Structures), Computer software, Computer-aided design, Computer-aided engineering, Design, Digital twin, Maintenance, Manufacturing systems, Modeling, Plant engineering (Facilities)
Proceedings Papers

Digital Twin Simulation and Optimization of Manufacturing Process Flows

Hankang Lee, Hui Yang
Proc. ASME. MSEC2023, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A013, June 12–16, 2023
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2023-105613
https://doi.org/10.1115/MSEC2023-105613
View Paper titled, Digital Twin Simulation and Optimization of Manufacturing Process Flows
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Topics: Digital twin, Experimental design, Flow (Dynamics), Manufacturing, Optimization, Simulation
Proceedings Papers

Multi-Criteria Decision-Making for Optimal Manufacturing Configuration Selection Using an Object-Oriented Data Model and Mathematical Formalization

Agajan Torayev, Zi Wang, Giovanna Martínez-Arellano, Jack C. Chaplin, David Sanderson, Svetan Ratchev
Proc. ASME. MSEC2023, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A012, June 12–16, 2023
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2023-105605
https://doi.org/10.1115/MSEC2023-105605
View Paper titled, Multi-Criteria Decision-Making for Optimal Manufacturing Configuration Selection Using an Object-Oriented Data Model and Mathematical Formalization
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Topics: Decision making, Manufacturing
Proceedings Papers

Online Cost-Effective Classification of Mixed Tool and Material Conditions in Ultrasonic Metal Welding: Towards Integrated Monitoring and Control

Kuan-Chieh Lu, Yuquan Meng, Zhiqiao Dong, Chenhui Shao
Proc. ASME. MSEC2023, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A007, June 12–16, 2023
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2023-104868
https://doi.org/10.1115/MSEC2023-104868
View Paper titled, Online Cost-Effective Classification of Mixed Tool and Material Conditions in Ultrasonic Metal Welding: Towards Integrated Monitoring and Control
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Topics: Metals, Real-time control, Welding
Proceedings Papers

Tracking and Visualization of Benchtop Assembly Components Using a RGBD Camera

Yashwanth Maddipatla, Jiaqiong Li, Yi Zheng, Beiwen Li
Proc. ASME. MSEC2023, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A006, June 12–16, 2023
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2023-104622
https://doi.org/10.1115/MSEC2023-104622
View Paper titled, Tracking and Visualization of Benchtop Assembly Components Using a RGBD Camera
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Topics: Manufacturing, Visualization, Computers, Engines, Flow (Dynamics), Lidar, Machine learning, Matlab, Network models, Printed circuit boards
Proceedings Papers

A Fast and Cost-Effective Imaging System for Fine-Scale Tool Condition Monitoring in Ultrasonic Metal Welding

Zhiqiao Dong, Qianmeng Chen, Kuan-Chieh Lu, Chenhui Shao
Proc. ASME. MSEC2023, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A008, June 12–16, 2023
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2023-104906
https://doi.org/10.1115/MSEC2023-104906
View Paper titled, A Fast and Cost-Effective Imaging System for Fine-Scale Tool Condition Monitoring in Ultrasonic Metal Welding
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Topics: Condition monitoring, Imaging, Maintenance, Metals, Metrology, Welding
Proceedings Papers

Transfer Learning for Predictive Quality in Laser-Induced Plasma Micro-Machining

Mengfei Chen, Rajiv Malhotra, Weihong “Grace” Guo
Proc. ASME. MSEC2023, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A015, June 12–16, 2023
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2023-106174
https://doi.org/10.1115/MSEC2023-106174
View Paper titled, Transfer Learning for Predictive Quality in Laser-Induced Plasma Micro-Machining
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Topics: Acoustic emissions, Lasers, Micromachining, Plasmas (Ionized gases)
Proceedings Papers

Stable Matching With Contracts for a Dynamic Two-Sided Manufacturing-as-a-Service (MaaS) Marketplace

Deepak Pahwa, Umut Dur, Binil Starly
Proc. ASME. MSEC2023, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A014, June 12–16, 2023
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2023-105876
https://doi.org/10.1115/MSEC2023-105876
View Paper titled, Stable Matching With Contracts for a Dynamic Two-Sided Manufacturing-as-a-Service (MaaS) Marketplace
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Topics: Design, Manufacturing
Proceedings Papers

A Human Robot Collaboration Framework for Assembly Tasks in High Mix Manufacturing Applications

Neel Dhanaraj, Niraj Ganesh, Rohit Gurav, Minseok Jeon, Omey M. Manyar, Santosh Narayan, Jaehyun Park, Zhao Yu, Satyandra K. Gupta
Proc. ASME. MSEC2023, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A011, June 12–16, 2023
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2023-105271
https://doi.org/10.1115/MSEC2023-105271
View Paper titled, A Human Robot Collaboration Framework for Assembly Tasks in High Mix Manufacturing Applications
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Topics: Human-robot collaboration, Manufacturing, Robots, Computers, Design, Mass production, Path planning, Satellites, Sensors, Simulation