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Proceedings Papers

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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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