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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

Improving Geometric Accuracy in Wire and Arc Additive Manufacturing With Engineering-Informed Machine Learning

Cesar Ruiz, Davoud Jafari, Vignesh Venkata Subramanian, Tom H. J. Vaneker, Wei Ya, Qiang Huang

Paper No: MSEC2022-85325

DOI: https://doi.org/10.1115/MSEC2022-85325

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Topics: Additive manufacturing, Machine learning, Shapes, Wire

Proceedings Papers

Smart Resin Vat: Real-Time Detecting Failures, Defects, and Curing Area in Vat Photopolymerization 3D Printing

Yujie Shan, Aravind Krishnakumar, Zehan Qin, Huachao Mao

Paper No: MSEC2022-85691

DOI: https://doi.org/10.1115/MSEC2022-85691

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Topics: Additive manufacturing, Failure, Hardening (Curing), Machine learning, Resins

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

Paper No: MSEC2022-85459

DOI: https://doi.org/10.1115/MSEC2022-85459

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Topics: Machine learning, Machinery, Manufacturing, Pulse width modulation, Maintenance, Manufacturing systems, Failure, Vibration, Artificial intelligence, Compressors

Proceedings Papers

Thin-Film Nitrate Sensor Performance Prediction Based on Image Analysis and Credibility Data to Enable a Certify As Built Framework

Xihui Wang, Ajanta Saha, Ye Mi, Ali Shakouri, Muhammad Ashraful Alam, George T. C. Chiu, Jan P. Allebach

Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T06A021, June 27–July 1, 2022

Paper No: MSEC2022-85638

DOI: https://doi.org/10.1115/MSEC2022-85638

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Topics: Sensors, Thin films, Machine learning, Testing, Data collection, Errors, Manufacturing, Membranes, Noise (Sound), Pipelines

Proceedings Papers

Machine Learning-Based Cutting Constant Estimation for Mechanistic Force Models of End Milling Operation

Shubham Vaishnav, K. A. Desai

Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T05A048, June 27–July 1, 2022

Paper No: MSEC2022-85587

DOI: https://doi.org/10.1115/MSEC2022-85587

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Topics: Cutting, Machine learning, Machinery, Milling

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

Physics-Informed Machine Learning for Accelerated Testing of Roll-to-Roll Printed Sensors

S. Chandra Mouli, Sotoudeh Sedaghat, Muhammed Ramazan Oduncu, Ajanta Saha, Rahim Rahimi, Muhammad A. Alam, Alexander Wei, Ali Shakouri, Bruno Ribeiro

Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T06A015, June 27–July 1, 2022

Paper No: MSEC2022-85392

DOI: https://doi.org/10.1115/MSEC2022-85392

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Topics: Machine learning, Physics, Printing, Sensors, Testing

Proceedings Papers

A Deterministic Inspection of Surface Preparation for Metalization

Shiva Shokri, Pooria Sedigh, Mehdi Hojjati, Tsz-Ho Kwok

Paper No: MSEC2022-85334

DOI: https://doi.org/10.1115/MSEC2022-85334

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Topics: Inspection, Surface preparation, Blasting, Coating processes, Coatings, Composite materials, Metals, Resins, Manufacturing, Microscopes

Proceedings Papers

Forecasting Repair and Maintenance Services of Medical Devices Using Support Vector Machine

Hao-yu Liao, Willie Cade, Sara Behdad

Proc. ASME. MSEC2021, Volume 1: Additive Manufacturing; Advanced Materials Manufacturing; Biomanufacturing; Life Cycle Engineering; Manufacturing Equipment and Automation, V001T04A008, June 21–25, 2021

Paper No: MSEC2021-63966

DOI: https://doi.org/10.1115/MSEC2021-63966

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Topics: Machine learning, Maintenance, Medical devices, Support vector machines

Proceedings Papers

Advanced Modeling of Drilling – Realistic Process Mechanics Leading to Helical Chip Formation

Wolfgang Lortz, Radu Pavel

Proc. ASME. MSEC2021, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T06A028, June 21–25, 2021

Paper No: MSEC2021-63790

DOI: https://doi.org/10.1115/MSEC2021-63790

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Topics: Drilling, Friction, Modeling, Temperature, Deformation, Metals, Wear, Artificial intelligence, Computers, Corners (Structural elements)

Proceedings Papers

Multiple Sound Sensors And Fusion In Modern CNN-Based Machine State Prediction

Eunseob Kim, Huitaek Yun, Martin Byung-Guk Jun, Kyunghyun Kim, Suk Won Cha

Paper No: MSEC2021-64036

DOI: https://doi.org/10.1115/MSEC2021-64036

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Topics: Artificial neural networks, Machine tools, Machinery, Sensors, Signals, Internet of things, Manufacturing, Acoustics, Bridges (Structures), Conveyor systems

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

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

A Machine Learning Approach to Model the Electrospinning Process of Biocompatible Materials

Juan Diego Toscano, Zebin Li, Luis Javier Segura, Hongyue Sun

Proc. ASME. MSEC2020, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T06A031, September 3, 2020

Paper No: MSEC2020-8362

DOI: https://doi.org/10.1115/MSEC2020-8362

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Topics: Biomaterials, Electrospinning, Machine learning, Modeling

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

Proceedings Papers

On Transfer Learning of Traditional Frequency and Time Domain Features in Turning

Melih C. Yesilli, Firas A. Khasawneh

Proc. ASME. MSEC2020, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A027, September 3, 2020

Paper No: MSEC2020-8274

DOI: https://doi.org/10.1115/MSEC2020-8274

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Topics: Accelerometers, Algorithms, Chatter, Cutting, Fast Fourier transforms, Machine learning, Manufacturing, Signal processing, Signals, Spectral energy distribution

Proceedings Papers

Fault Diagnosis of Timed Event Systems: An Exploration of Machine Learning Methods

Joseph Cohen, Baoyang Jiang, Jun Ni

Proc. ASME. MSEC2020, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A029, September 3, 2020

Paper No: MSEC2020-8360

DOI: https://doi.org/10.1115/MSEC2020-8360

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Topics: Fault diagnosis, Machine learning, Principal component analysis, Programmable controllers, Algorithms, Signals, Artificial neural networks, Failure, Integrated circuit fabrication, Manufacturing

Proceedings Papers

Machine Learning Based Novelty Detection Methods for Progressive Stamping Process Health Monitoring

Tianchen Qiu, Xingjian Lai, Jun Ni

Proc. ASME. MSEC2020, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A034, September 3, 2020

Paper No: MSEC2020-8496

DOI: https://doi.org/10.1115/MSEC2020-8496

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Topics: Machine learning, Machinery, Metal stamping, Support vector machines

Proceedings Papers

Geometric Accuracy Prediction for Additive Manufacturing Through Machine Learning of Triangular Mesh Data

Nathan Decker, Qiang Huang

Proc. ASME. MSEC2019, Volume 1: Additive Manufacturing; Manufacturing Equipment and Systems; Bio and Sustainable Manufacturing, V001T02A043, June 10–14, 2019

Paper No: MSEC2019-3050

DOI: https://doi.org/10.1115/MSEC2019-3050

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Topics: Additive manufacturing, Machine learning, Modeling, Shapes, Errors, Geometry, Printing, Trains

NARROW

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

Improving Geometric Accuracy in Wire and Arc Additive Manufacturing With Engineering-Informed Machine Learning

Smart Resin Vat: Real-Time Detecting Failures, Defects, and Curing Area in Vat Photopolymerization 3D Printing

Anomaly Scoring Model for Diagnosis on Machine Condition and Health Management

Thin-Film Nitrate Sensor Performance Prediction Based on Image Analysis and Credibility Data to Enable a Certify As Built Framework

Machine Learning-Based Cutting Constant Estimation for Mechanistic Force Models of End Milling Operation

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

Physics-Informed Machine Learning for Accelerated Testing of Roll-to-Roll Printed Sensors

A Deterministic Inspection of Surface Preparation for Metalization

Forecasting Repair and Maintenance Services of Medical Devices Using Support Vector Machine

Advanced Modeling of Drilling – Realistic Process Mechanics Leading to Helical Chip Formation

Multiple Sound Sensors And Fusion In Modern CNN-Based Machine State Prediction

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

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

A Machine Learning Approach to Model the Electrospinning Process of Biocompatible Materials

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

On Transfer Learning of Traditional Frequency and Time Domain Features in Turning

Fault Diagnosis of Timed Event Systems: An Exploration of Machine Learning Methods

Machine Learning Based Novelty Detection Methods for Progressive Stamping Process Health Monitoring

Geometric Accuracy Prediction for Additive Manufacturing Through Machine Learning of Triangular Mesh Data

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