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Journal Articles

Knowledge Discovery in Engineering Applications Using Machine Learning Techniques

Christian Kubik, Dirk Alexander Molitor, Marco Becker, Peter Groche

J. Manuf. Sci. Eng. September 2022, 144(9): 091003.

Paper No: MANU-21-1397

DOI: https://doi.org/10.1115/1.4054158

Published Online: April 8, 2022

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Topics: Blanking (Metalworking), Chain, Data acquisition, Data mining, Engineering systems and industry applications, Machine learning, Manufacturing, Manufacturing systems, Modeling, Sensors

Journal Articles

Machine Learning for Diagnosis of Event Synchronization Faults in Discrete Manufacturing Systems

Joseph Cohen, Baoyang Jiang, Jun Ni

J. Manuf. Sci. Eng. July 2022, 144(7): 071006.

Paper No: MANU-21-1315

DOI: https://doi.org/10.1115/1.4052762

Published Online: December 8, 2021

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Topics: Fault diagnosis, Machine learning, Signals, Synchronization, Failure, Manufacturing systems, Programmable controllers, Delays

Journal Articles

Semi-Supervised Learning for Anomaly Classification Using Partially Labeled Subsets

Joseph Cohen, Jun Ni

J. Manuf. Sci. Eng. June 2022, 144(6): 061008.

Paper No: MANU-21-1317

DOI: https://doi.org/10.1115/1.4052761

Published Online: December 3, 2021

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Topics: Algorithms, Computer-aided engineering, Dimensions, Feature extraction, Machine learning, Principal component analysis, Integrated circuit fabrication, Artificial intelligence

Journal Articles

In-Situ Calibrated Digital Process Twin Models for Resource Efficient Manufacturing

David Adeniji, Julius Schoop

J. Manuf. Sci. Eng. April 2022, 144(4): 041008.

Paper No: MANU-21-1321

DOI: https://doi.org/10.1115/1.4052131

Published Online: September 27, 2021

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Topics: Machining, Manufacturing, Titanium aluminide, Modeling, Physics, Pressure, Product quality, Energy efficiency, Aerospace industry, Turbine blades

Journal Articles

A Study on Using Image-Based Machine Learning Methods to Develop Surrogate Models of Stamp Forming Simulations

Haosu Zhou, Qingfeng Xu, Zhenguo Nie, Nan Li

J. Manuf. Sci. Eng. February 2022, 144(2): 021012.

Paper No: MANU-21-1029

DOI: https://doi.org/10.1115/1.4051604

Published Online: August 6, 2021

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Topics: Design, Engineering simulation, Finite element analysis, Machine learning, Multilayer perceptron, Scalars, Simulation, Interpolation, Metalworking, Simulation results

Journal Articles

Improving Production Performance Through Multi-Plant Cross Learning

Jing Huang, Qing Chang, Yu Qian, Jorge Arinez, Guoxian Xiao

J. Manuf. Sci. Eng. January 2022, 144(1): 014501.

Paper No: MANU-19-1700

DOI: https://doi.org/10.1115/1.4050543

Published Online: July 6, 2021

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Topics: Machine learning, Machinery, Assembly lines

Journal Articles

Toward Sub-Surface Pore Prediction Capabilities for Laser Powder Bed Fusion Using Data Science

Deniz Sera Ertay, Shima Kamyab, Mihaela Vlasea, Zohreh Azimifar, Thanh Ma, Allan D. Rogalsky, Paul Fieguth

J. Manuf. Sci. Eng. July 2021, 143(7): 071016.

Paper No: MANU-21-1016

DOI: https://doi.org/10.1115/1.4050461

Published Online: March 26, 2021

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Topics: Algorithms, Artificial neural networks, Computerized tomography, Lasers, Machine learning, Additive manufacturing, Porosity

Journal Articles

Tool Life Stage Prediction in Micro-Milling From Force Signal Analysis Using Machine Learning Methods

Alwin Varghese, Vinay Kulkarni, Suhas S. Joshi

J. Manuf. Sci. Eng. May 2021, 143(5): 054501.

Paper No: MANU-20-1137

DOI: https://doi.org/10.1115/1.4048636

Published Online: November 11, 2020

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Topics: Condition monitoring, Cutting, Machine learning, Machining, Micromilling, Model development, Signals, Wear

Journal Articles

Mitigating Scattering Effects in Light-Based Three-Dimensional Printing Using Machine Learning

Shangting You, Jiaao Guan, Jeffrey Alido, Henry H. Hwang, Ronald Yu, Leilani Kwe, Hao Su, Shaochen Chen

J. Manuf. Sci. Eng. August 2020, 142(8): 081002.

Paper No: MANU-19-1644

DOI: https://doi.org/10.1115/1.4046986

Published Online: May 14, 2020

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Topics: Additive manufacturing, Artificial neural networks, Electromagnetic scattering, Printing, Machine learning, Manufacturing, Radiation scattering, Scattering (Physics), Resolution (Optics)

Journal Articles

Acoustic Emission Characterization of Natural Fiber Reinforced Plastic Composite Machining Using a Random Forest Machine Learning Model

Zimo Wang, Faissal Chegdani, Neehar Yalamarti, Behrouz Takabi, Bruce Tai, Mohamed El Mansori, Satish Bukkapatnam

J. Manuf. Sci. Eng. March 2020, 142(3): 031003.

Paper No: MANU-19-1219

DOI: https://doi.org/10.1115/1.4045945

Published Online: January 31, 2020

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Topics: Acoustic emissions, Composite materials, Cutting, Fibers, Fracture (Materials), Machining, Signals, Fracture (Process), Sensors, Fiber reinforced plastics

Includes: Supplementary data

Journal Articles

Focus Variation Measurement and Prediction of Surface Texture Parameters Using Machine Learning in Laser Powder Bed Fusion

Tuğrul Özel, Ayça Altay, Bilgin Kaftanoğlu, Richard Leach, Nicola Senin, Alkan Donmez

J. Manuf. Sci. Eng. January 2020, 142(1): 011008.

Paper No: MANU-19-1085

DOI: https://doi.org/10.1115/1.4045415

Published Online: November 22, 2019

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Topics: Artificial neural networks, Density, Lasers, Machine learning, Surface texture, Computer programming, Rotation

Journal Articles

A Framework for the Capture and Analysis of Product Usage Data for Continuous Product Improvement

Henning Voet, Max Altenhof, Max Ellerich, Robert H. Schmitt, Barbara Linke

J. Manuf. Sci. Eng. February 2019, 141(2): 021010.

Paper No: MANU-18-1278

DOI: https://doi.org/10.1115/1.4041948

Published Online: December 24, 2018

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Topics: Classification, Design, Sensors, Product development, Data collection, Grinding, Machine learning, Measurement systems, Internet of things

Journal Articles

Cloud-Based Parallel Machine Learning for Tool Wear Prediction

Dazhong Wu, Connor Jennings, Janis Terpenny, Soundar Kumara, Robert X. Gao

J. Manuf. Sci. Eng. April 2018, 140(4): 041005.

Paper No: MANU-17-1344

DOI: https://doi.org/10.1115/1.4038002

Published Online: February 12, 2018

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Topics: Algorithms, Machine learning, Wear, Manufacturing, Milling, Cloud computing, Cutting, Sensors, Vibration

Journal Articles

Quantifying Geometric Accuracy With Unsupervised Machine Learning: Using Self-Organizing Map on Fused Filament Fabrication Additive Manufacturing Parts

Mojtaba Khanzadeh, Prahalada Rao, Ruholla Jafari-Marandi, Brian K. Smith, Mark A. Tschopp, Linkan Bian

J. Manuf. Sci. Eng. March 2018, 140(3): 031011.

Paper No: MANU-17-1366

DOI: https://doi.org/10.1115/1.4038598

Published Online: December 21, 2017

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Topics: Additive manufacturing, Lasers, Machine learning, Manufacturing, Modeling, Self-organization, Shapes, Temperature

Journal Articles

Classifying the Dimensional Variation in Additive Manufactured Parts From Laser-Scanned Three-Dimensional Point Cloud Data Using Machine Learning Approaches

M. Samie Tootooni, Ashley Dsouza, Ryan Donovan, Prahalad K. Rao, Zhenyu (James) Kong, Peter Borgesen

J. Manuf. Sci. Eng. September 2017, 139(9): 091005.

Paper No: MANU-17-1073

DOI: https://doi.org/10.1115/1.4036641

Published Online: June 22, 2017

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Topics: Additive manufacturing, Design, Eigenvalues, Lasers, Machine learning

Journal Articles

A Comparative Study on Machine Learning Algorithms for Smart Manufacturing: Tool Wear Prediction Using Random Forests

Dazhong Wu, Connor Jennings, Janis Terpenny, Robert X. Gao, Soundar Kumara

J. Manuf. Sci. Eng. July 2017, 139(7): 071018.

Paper No: MANU-16-1567

DOI: https://doi.org/10.1115/1.4036350

Published Online: April 18, 2017

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Topics: Algorithms, Artificial neural networks, Wear, Machine learning

Journal Articles

Building Layered Models to Support Engineering Decision Making: A Machine Learning Approach

S. C.-Y. Lu, D. K. Tcheng

J. Manuf. Sci. Eng. February 1991, 113(1): 1–9.

DOI: https://doi.org/10.1115/1.2899617

Published Online: February 1, 1991

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Topics: Decision making, Machine learning, Modeling, Cutting, Engineering design, Engineering prototypes, Inspection, Optimization, Physics, Process design

Journal citation

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Supplemental Material

Knowledge Discovery in Engineering Applications Using Machine Learning Techniques

Machine Learning for Diagnosis of Event Synchronization Faults in Discrete Manufacturing Systems

Semi-Supervised Learning for Anomaly Classification Using Partially Labeled Subsets

In-Situ Calibrated Digital Process Twin Models for Resource Efficient Manufacturing

A Study on Using Image-Based Machine Learning Methods to Develop Surrogate Models of Stamp Forming Simulations

Improving Production Performance Through Multi-Plant Cross Learning

Toward Sub-Surface Pore Prediction Capabilities for Laser Powder Bed Fusion Using Data Science

Tool Life Stage Prediction in Micro-Milling From Force Signal Analysis Using Machine Learning Methods

Mitigating Scattering Effects in Light-Based Three-Dimensional Printing Using Machine Learning

Acoustic Emission Characterization of Natural Fiber Reinforced Plastic Composite Machining Using a Random Forest Machine Learning Model

Focus Variation Measurement and Prediction of Surface Texture Parameters Using Machine Learning in Laser Powder Bed Fusion

A Framework for the Capture and Analysis of Product Usage Data for Continuous Product Improvement

Cloud-Based Parallel Machine Learning for Tool Wear Prediction

Quantifying Geometric Accuracy With Unsupervised Machine Learning: Using Self-Organizing Map on Fused Filament Fabrication Additive Manufacturing Parts

Classifying the Dimensional Variation in Additive Manufactured Parts From Laser-Scanned Three-Dimensional Point Cloud Data Using Machine Learning Approaches

A Comparative Study on Machine Learning Algorithms for Smart Manufacturing: Tool Wear Prediction Using Random Forests

Building Layered Models to Support Engineering Decision Making: A Machine Learning Approach

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