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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
Paper No: MSEC2022-78324
DOI: https://doi.org/10.1115/MSEC2022-78324
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Topics: Iterative learning control, Modeling, Dimensions, Errors, Warping, Additive manufacturing, Algorithms, Engineering prototypes, Extruding, Manufacturing
Proceedings Papers

Acoustic Process Monitoring of Contact Tip to Work Piece Distance in Wire Arc Additive Manufacturing by Random Forest Algorithms

Dylan Hebert, Austen Thien, Christopher Saldana
Proc. ASME. MSEC2022, Volume 1: Additive Manufacturing; Biomanufacturing; Life Cycle Engineering; Manufacturing Equipment and Automation; Nano/Micro/Meso Manufacturing, V001T01A020, June 27–July 1, 2022
Paper No: MSEC2022-85404
DOI: https://doi.org/10.1115/MSEC2022-85404
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Topics: Acoustics, Additive manufacturing, Algorithms, Machine learning, Process monitoring, Wire
Proceedings Papers

Trajectory Control of 6-DOF Welding Robot Based on STM32

Dingzhong Li, Hong Lu, Yongquan Zhang, Zidong Wu, He Huang, Meng Liu, Shaojun Wang
Proc. ASME. MSEC2022, Volume 1: Additive Manufacturing; Biomanufacturing; Life Cycle Engineering; Manufacturing Equipment and Automation; Nano/Micro/Meso Manufacturing, V001T04A007, June 27–July 1, 2022
Paper No: MSEC2022-85494
DOI: https://doi.org/10.1115/MSEC2022-85494
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Topics: Algorithms, Robots, Trajectories (Physics), Welding
Proceedings Papers

Pass-Wise Tool Wear Prediction in Turning Based on Long-Short Term Memory Algorithm Using Current Signals

Benvolence Chinomona, Chunhui Chung, Po-Chieh Wang
Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T05A031, June 27–July 1, 2022
Paper No: MSEC2022-85339
DOI: https://doi.org/10.1115/MSEC2022-85339
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Topics: Algorithms, Signals, Turning, Wear
Proceedings Papers

Finding Robust Pareto-Optimal Solutions Over Time for Dynamic Disassembly Sequence Planning

Xin Zhang, Yilin Fang, Quan Liu
Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T06A012, June 27–July 1, 2022
Paper No: MSEC2022-85358
DOI: https://doi.org/10.1115/MSEC2022-85358
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Topics: Algorithms, Optimization, Pareto optimization, Uncertainty
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
Paper No: MSEC2022-85269
DOI: https://doi.org/10.1115/MSEC2022-85269
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Topics: Algorithms, Computer software, Errors, Hardware, Human-robot collaboration, Human-robot interaction, Manufacturing, Manufacturing systems, Pipes, Sensors
Proceedings Papers

Individual-Based Transfer Learning for Dynamic Human-Robot Collaborative Disassembly Line Balancing

Yilin Fang, Xiao Zhang
Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T06A013, June 27–July 1, 2022
Paper No: MSEC2022-85362
DOI: https://doi.org/10.1115/MSEC2022-85362
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Topics: Optimization, Robots, Algorithms, Product quality, Uncertainty, Human-robot collaboration, Optimization algorithms
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
Paper No: MSEC2022-82773
DOI: https://doi.org/10.1115/MSEC2022-82773
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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
Proceedings Papers

Curating Datasets of Flexible Assemblies to Predict Spring-Back Behavior for Machine Learning Purposes

Alex Adrian, Satchit Ramnath, Sai Chandu Sunkara, Yannis Korkolis, Joseph K. Davidson, Jami J. Shah
Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T06A025, June 27–July 1, 2022
Paper No: MSEC2022-85718
DOI: https://doi.org/10.1115/MSEC2022-85718
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Topics: Finite element analysis, Joining, Machine learning, Metal stamping, Sheet metal, Springs, Workflow, Simulation, Manufacturing, Design
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
Paper No: MSEC2021-62056
DOI: https://doi.org/10.1115/MSEC2021-62056
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Topics: Algorithms, Manufacturing systems, Sensors, Trajectories (Physics), Wireless sensor networks
Proceedings Papers

A Flexible Similarity Based Algorithm for Tool Condition Monitoring

Ben Stuhr, Rui Liu
Proc. ASME. MSEC2021, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T06A012, June 21–25, 2021
Paper No: MSEC2021-62021
DOI: https://doi.org/10.1115/MSEC2021-62021
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Topics: Algorithms, Condition monitoring, Manufacturing, Signals
Proceedings Papers

Robotic Grasping Training Using Deep Reinforcement Learning With Policy Guidance Mechanism

Junying Yao, Yongkui Liu, Tingyu Lin, Xubin Ping, He Xu, Wenxiao Wang, Yingying Xiao, Lin Zhang, Lihui Wang
Proc. ASME. MSEC2021, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A015, June 21–25, 2021
Paper No: MSEC2021-63974
DOI: https://doi.org/10.1115/MSEC2021-63974
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Topics: Grasping, Platinum group metals, Reinforcement learning, Robots, Algorithms, Engineering simulation, Manufacturing, Simulation
Proceedings Papers

Functional Fiber Junctions for Circuit Routing in E-Textiles: Deterministic Alignment of MEMS Layout With Fabric Structure

Sushmita Challa, M. Shafquatul Islam, Danming Wei, Jasmin Beharic, Dan O. Popa, C. K. Harnett
Proc. ASME. MSEC2021, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T08A009, June 21–25, 2021
Paper No: MSEC2021-63887
DOI: https://doi.org/10.1115/MSEC2021-63887
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Topics: Algorithms, Circuits, Fibers, Junctions, Microelectromechanical systems, Textiles
Proceedings Papers

A Semi-Supervised Multiclass Anomaly Detection Approach for Partially Labeled In-Process Measurement Data

Joseph Cohen, Jun Ni
Proc. ASME. MSEC2021, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T09A004, June 21–25, 2021
Paper No: MSEC2021-63465
DOI: https://doi.org/10.1115/MSEC2021-63465
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Topics: Algorithms, Artificial intelligence, Dimensions, Feature extraction, Flaw detection, Integrated circuit fabrication, Machine learning, Principal component analysis
Proceedings Papers

Toolpath Generation for Additive Manufacturing Considering Structural Performance

Eder Sales, Tsz Ho Kwok, Yong Chen
Proc. ASME. MSEC2020, Volume 1: Additive Manufacturing; Advanced Materials Manufacturing; Biomanufacturing; Life Cycle Engineering; Manufacturing Equipment and Automation, V001T01A035, September 3, 2020
Paper No: MSEC2020-8413
DOI: https://doi.org/10.1115/MSEC2020-8413
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Topics: Additive manufacturing, Optimization, Computer-aided design, Topology, Parallel strand lumber, Algorithms, Manufacturing, Shapes, Stress, Structural design
Proceedings Papers

Autonomous Manufacturing Using Machine Learning: A Computational Case Study With a Limited Manufacturing Budget

Md. Ferdous Alam, Max Shtein, Kira Barton, David J. Hoelzle
Proc. ASME. MSEC2020, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A009, September 3, 2020
Paper No: MSEC2020-8472
DOI: https://doi.org/10.1115/MSEC2020-8472
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Topics: Machine learning, Manufacturing, Algorithms, Design, Manufacturing systems, Acoustics, Phononic crystals, Spectra (Spectroscopy)
Proceedings Papers

Simulation of Complex Plastic Flows in Machining of Metal Polycrystals Using Remeshing

Vandana A. Salilkumar, Narayan K. Sundaram
Proc. ASME. MSEC2020, Volume 1: Additive Manufacturing; Advanced Materials Manufacturing; Biomanufacturing; Life Cycle Engineering; Manufacturing Equipment and Automation, V001T05A003, September 3, 2020
Paper No: MSEC2020-8255
DOI: https://doi.org/10.1115/MSEC2020-8255
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Topics: Flow (Dynamics), Machining, Metals, Simulation, Cutting, Separation (Technology), Friction, Imaging, Algorithms, Copper
Proceedings Papers

Incorporating Tool Contact Considerations in Tool-Path Planning for Robotic Operations

Prahar M. Bhatt, Cheng Gong, Ariyan M. Kabir, Rishi K. Malhan, Brual C. Shah, Satyandra K. Gupta
Proc. ASME. MSEC2020, Volume 1: Additive Manufacturing; Advanced Materials Manufacturing; Biomanufacturing; Life Cycle Engineering; Manufacturing Equipment and Automation, V001T05A018, September 3, 2020
Paper No: MSEC2020-8522
DOI: https://doi.org/10.1115/MSEC2020-8522
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Topics: Algorithms, Degrees of freedom, Generators, Geometry, Manipulators, Manufacturing, Path planning, Robotics, Trajectories (Physics)
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
Paper No: MSEC2020-8290
DOI: https://doi.org/10.1115/MSEC2020-8290
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Topics: Manufacturing cells, Optimization, Transportation systems, Vehicles, Manufacturing systems, Algorithms, Machinery, Manufacturing, Pareto optimization
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
Paper No: MSEC2020-8261
DOI: https://doi.org/10.1115/MSEC2020-8261
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Topics: Artificial neural networks, Inspection, Algorithms, Flaw detection, Machine learning, Manufacturing systems, Support vector machines, Visualization