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Proceedings Papers

A Simulated Evaluation of Powder Flowability Through a Partially Obstructed Consumable in Blown Powder Directed Energy Deposition Systems

Lisa DeWitte, Katherine Fu
Proc. ASME. MSEC2024, Volume 1: Additive Manufacturing; Advanced Materials Manufacturing; Biomanufacturing; Life Cycle Engineering, V001T01A010, June 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2024-122672
https://doi.org/10.1115/MSEC2024-122672
View Paper titled, A Simulated Evaluation of Powder Flowability Through a Partially Obstructed Consumable in Blown Powder Directed Energy Deposition Systems
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Topics: Additive manufacturing, Bridges (Structures), Cladding systems (Building), Computational fluid dynamics, Economics , Failure, Flow (Dynamics), Gas flow, Geometry, Machine tools
Proceedings Papers

A Mobile Additive Manufacturing Robot Framework for Smart Manufacturing Systems

Yifei Li, Jeongwon Park, Guha Manogharan, Feng Ju, Ilya Kovalenko
Proc. ASME. MSEC2024, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality & Reliability, V002T05A010, June 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2024-125413
https://doi.org/10.1115/MSEC2024-125413
View Paper titled, A Mobile Additive Manufacturing Robot Framework for Smart Manufacturing Systems
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Topics: Additive manufacturing, Manufacturing, Manufacturing systems, Robotics, Robots
Proceedings Papers

A Bayesian Network-Based Control Charting Framework for Identifying the Root Causes of Process Shifts in Multistage Manufacturing Systems

Partha Protim Mondal, Placid M. Ferreira, Shiv G. Kapoor, Patrick N. Bless
Proc. ASME. MSEC2024, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality & Reliability, V002T09A001, June 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2024-130229
https://doi.org/10.1115/MSEC2024-130229
View Paper titled, A Bayesian Network-Based Control Charting Framework for Identifying the Root Causes of Process Shifts in Multistage Manufacturing Systems
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Topics: Bayesian network, Manufacturing systems
Proceedings Papers

Positioning Accuracy in a Concurrent Robot-CNC Hybrid Manufacturing System

Jesse Goodwin, Kathryn Kelly, Melissa Foley, Christopher Saldana, Thomas Kurfess, Kyle Saleeby
Proc. ASME. MSEC2024, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality & Reliability, V002T05A001, June 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2024-121212
https://doi.org/10.1115/MSEC2024-121212
View Paper titled, Positioning Accuracy in a Concurrent Robot-CNC Hybrid Manufacturing System
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Topics: Additive manufacturing, Computer numerical control machine tools, Manufacturing, Manufacturing systems, Robots, Machinery, Machining, Errors, Assembly lines, Control equipment
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

Comparison of Reinforcement Learning Methods for Production Control in Discrete Manufacturing Systems

Lingxiang Yun, Jingwen Wang, Minkun Xiao, Lin Li
Proc. ASME. MSEC2023, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A004, June 12–16, 2023
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2023-104452
https://doi.org/10.1115/MSEC2023-104452
View Paper titled, Comparison of Reinforcement Learning Methods for Production Control in Discrete Manufacturing Systems
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Topics: Manufacturing systems, Production control, Reinforcement learning
Proceedings Papers

Review of Recent Methods and Learning Techniques in Prediction of Tool Life

Ulfa Fairuz Izdihar, Brijesh Patel, Zih Fong Huang, Chih-Ho Yeh, Po Ting Lin
Proc. ASME. MSEC2023, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T09A002, June 12–16, 2023
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2023-101060
https://doi.org/10.1115/MSEC2023-101060
View Paper titled, Review of Recent Methods and Learning Techniques in Prediction of Tool Life
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Topics: Alloy steel, Chatter, Computer numerical control machine tools, Condition monitoring, Cutting, Cutting tools, Data acquisition, Drilling, Failure, Feature extraction
Proceedings Papers

FPGA-Based Edge Computing Framework: Modeling of Computation Task Scheduling

Jianfei Tan, Hao Yang, Chun Zhao, Lin Zhang
Proc. ASME. MSEC2023, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A003, June 12–16, 2023
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2023-104323
https://doi.org/10.1115/MSEC2023-104323
View Paper titled, FPGA-Based Edge Computing Framework: Modeling of Computation Task Scheduling
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Topics: Computation, Manufacturing, Modeling, Stress, Manufacturing systems, Algorithms, Cloud computing, Collaboration, Cycles, Design
Proceedings Papers

Anomaly Scoring Model for Diagnosis on Machine Condition and Health Management

Byung Gun Joung, Zhongtian Li, John W. Sutherland
Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T06A017, June 27–July 1, 2022
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2022-85459
https://doi.org/10.1115/MSEC2022-85459
View Paper titled, Anomaly Scoring Model for Diagnosis on Machine Condition and Health Management
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Topics: Machine learning, Machinery, Manufacturing, Pulse width modulation, Maintenance, Manufacturing systems, Failure, Vibration, Artificial intelligence, Compressors
Proceedings Papers

Comparison of Human Skeleton Trackers Paired With a Novel Skeleton Fusion Algorithm

Jared T. Flowers, Gloria J. Wiens
Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T06A010, June 27–July 1, 2022
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2022-85269
https://doi.org/10.1115/MSEC2022-85269
View Paper titled, Comparison of Human Skeleton Trackers Paired With a Novel Skeleton Fusion Algorithm
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Topics: Algorithms, Computer software, Errors, Hardware, Human-robot collaboration, Human-robot interaction, Manufacturing, Manufacturing systems, Pipes, Sensors
Proceedings Papers

Proof of Authenticity Statistics From Multiple Perceptual Hash Comparisons: A Case Study

Michele Maasberg, Leslie G. Butler, Brendan Birch, Maia Trailer
Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T06A004, June 27–July 1, 2022
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2022-83923
https://doi.org/10.1115/MSEC2022-83923
View Paper titled, Proof of Authenticity Statistics From Multiple Perceptual Hash Comparisons: A Case Study
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Topics: Additive manufacturing, Aerospace industry, Blockchain technology, Computation, Dust, Fractals, Lasers, Manufacturing industry, Manufacturing systems, Melting
Proceedings Papers

Using Iterative Learning Control to Improve the Accuracy of Desktop Fused Deposition Modeling Printers: An Experimental Case Study

Lawrence Funke, Matthew Opara
Proc. ASME. MSEC2022, Volume 1: Additive Manufacturing; Biomanufacturing; Life Cycle Engineering; Manufacturing Equipment and Automation; Nano/Micro/Meso Manufacturing, V001T01A001, June 27–July 1, 2022
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2022-78324
https://doi.org/10.1115/MSEC2022-78324
View Paper titled, Using Iterative Learning Control to Improve the Accuracy of Desktop Fused Deposition Modeling Printers: An Experimental Case Study
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Topics: Iterative learning control, Modeling, Dimensions, Errors, Warping, Additive manufacturing, Algorithms, Engineering prototypes, Extruding, Manufacturing
Proceedings Papers

Collaborative Platform for Remote Manufacturing Systems Using Industrial Internet and Digital Twin in the COVID-19 Era

Jay Lee, Xiaodong Jia, Qibo Yang, Keyi Sun, Xiang Li
Proc. ASME. MSEC2021, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A018, June 21–25, 2021
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2021-64237
https://doi.org/10.1115/MSEC2021-64237
View Paper titled, Collaborative Platform for Remote Manufacturing Systems Using Industrial Internet and Digital Twin in the COVID-19 Era
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Topics: Internet, Manufacturing, Manufacturing systems
Proceedings Papers

Optimal Sensor Deployment to Diagnose Large-Scale Manufacturing Systems Using a Convergence-Trajectory Controlled Ant Colony System Algorithm

Rajshekhar Singhania, Chinmay Sawkar, Manoj K. Tiwari
Proc. ASME. MSEC2021, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T09A002, June 21–25, 2021
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2021-62056
https://doi.org/10.1115/MSEC2021-62056
View Paper titled, Optimal Sensor Deployment to Diagnose Large-Scale Manufacturing Systems Using a Convergence-Trajectory Controlled Ant Colony System Algorithm
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Topics: Algorithms, Manufacturing systems, Sensors, Trajectories (Physics), Wireless sensor networks
Proceedings Papers

Multi-Agent-Based Self-Organizing Manufacturing Network Towards Mass Personalization

Zhaojun Qin, Yuqian Lu
Proc. ASME. MSEC2021, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A016, June 21–25, 2021
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2021-63990
https://doi.org/10.1115/MSEC2021-63990
View Paper titled, Multi-Agent-Based Self-Organizing Manufacturing Network Towards Mass Personalization
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Topics: Manufacturing, Manufacturing systems, Self-organization
Proceedings Papers

A Data-Driven Proactive Scheduling Approach for Hybrid Flow Shop Scheduling Problem

Dong Han, Wangming Li, Xinyu Li, Liang Gao, Yang Li
Proc. ASME. MSEC2021, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A002, June 21–25, 2021
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2021-61672
https://doi.org/10.1115/MSEC2021-61672
View Paper titled, A Data-Driven Proactive Scheduling Approach for Hybrid Flow Shop Scheduling Problem
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Topics: Flow (Dynamics), Manufacturing, Machinery, Stability, Breakdown (Electricity), Design, Manufacturing industry, Manufacturing systems, Optimization algorithms, Pandemics
Proceedings Papers

SQL and NoSQL Databases for Cyber Physical Production Systems in Internet of Things for Manufacturing (IoTfM)

David Gamero, Andrew Dugenske, Thomas Kurfess, Christopher Saldana, Katherine Fu
Proc. ASME. MSEC2021, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A014, June 21–25, 2021
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2021-63960
https://doi.org/10.1115/MSEC2021-63960
View Paper titled, SQL and NoSQL Databases for Cyber Physical Production Systems in Internet of Things for Manufacturing (IoTfM)
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Topics: Databases, Internet of things, Manufacturing, Manufacturing systems, Relational databases
Proceedings Papers

Inter-Cell Scheduling Optimization With Limited Transportation Capacities for Optimization of Vehicle Numbers

Qiong Liu, Qin Ye, Xu Mei
Proc. ASME. MSEC2020, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A003, September 3, 2020
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2020-8290
https://doi.org/10.1115/MSEC2020-8290
View Paper titled, Inter-Cell Scheduling Optimization With Limited Transportation Capacities for Optimization of Vehicle Numbers
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Topics: Manufacturing cells, Optimization, Transportation systems, Vehicles, Manufacturing systems, Algorithms, Machinery, Manufacturing, Pareto optimization
Proceedings Papers

Safety Strategy in the Smart Manufacturing System: A Human Robot Collaboration Case Study

Xi Vincent Wang, Lihui Wang
Proc. ASME. MSEC2020, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A026, September 3, 2020
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2020-8427
https://doi.org/10.1115/MSEC2020-8427
View Paper titled, Safety Strategy in the Smart Manufacturing System: A Human Robot Collaboration Case Study
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Topics: Collaboration, Manufacturing systems, Robots, Safety
Proceedings Papers

Edge Computing Accelerated Defect Classification Based on Deep Convolutional Neural Network With Application in Rolling Image Inspection

Jiayu Huang, Nurretin Sergin, Akshay Dua, Erfan Bank Tavakoli, Hao Yan, Fengbo Ren, Feng Ju
Proc. ASME. MSEC2020, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A037, September 3, 2020
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2020-8261
https://doi.org/10.1115/MSEC2020-8261
View Paper titled, Edge Computing Accelerated Defect Classification Based on Deep Convolutional Neural Network With Application in Rolling Image Inspection
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Topics: Artificial neural networks, Inspection, Algorithms, Flaw detection, Machine learning, Manufacturing systems, Support vector machines, Visualization