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Journal Articles

Indirect Tool Condition Monitoring Using Ensemble Machine Learning Techniques

Alexandra Schueller, Christopher Saldaña
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Research Papers
J. Manuf. Sci. Eng. January 2023, 145(1): 011006.
Paper No: MANU-22-1333
https://doi.org/10.1115/1.4055822
Published Online: October 13, 2022
View Article titled, Indirect Tool Condition Monitoring Using Ensemble Machine Learning Techniques
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Topics: Condition monitoring, Machine learning, Machining, Wear, Signals, Robustness, Stress
Journal Articles

Condition Monitoring of Machine Tool Feed Drives: A Review

Quade Butler, Youssef Ziada, David Stephenson, S. Andrew Gadsden
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Review Articles
J. Manuf. Sci. Eng. October 2022, 144(10): 100802.
Paper No: MANU-21-1529
https://doi.org/10.1115/1.4054516
Published Online: June 22, 2022
View Article titled, Condition Monitoring of Machine Tool Feed Drives: A Review
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Topics: Condition monitoring, Machine tools, Screws, Sensors, Signals, Wear, Vibration, Machinery, Errors
Journal Articles

Procedural Guide for System-Level Impact Evaluation of Industrial Artificial Intelligence-Driven Technologies: Application to Risk-Based Investment Analysis for Condition Monitoring Systems in Manufacturing

Michael Sharp, Mehdi Dadfarnia, Timothy Sprock, Douglas Thomas
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Research Papers
J. Manuf. Sci. Eng. July 2022, 144(7): 071008.
Paper No: MANU-21-1018
https://doi.org/10.1115/1.4053155
Published Online: December 16, 2021
View Article titled, Procedural Guide for System-Level Impact Evaluation of Industrial Artificial Intelligence-Driven Technologies: Application to Risk-Based Investment Analysis for Condition Monitoring Systems in Manufacturing
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Topics: Condition monitoring, Risk
Journal Articles

A Flexible Similarity-Based Algorithm for Tool Condition Monitoring

Benjamin Stuhr, Rui Liu
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Research Papers
J. Manuf. Sci. Eng. March 2022, 144(3): 031010.
Paper No: MANU-21-1328
https://doi.org/10.1115/1.4051885
Published Online: August 19, 2021
View Article titled, A Flexible Similarity-Based Algorithm for Tool Condition Monitoring
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Topics: Algorithms, Condition monitoring, Cutting, Cutting tools, Machining, Signals, Wear
Journal Articles

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

Alwin Varghese, Vinay Kulkarni, Suhas S. Joshi
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Technical Briefs
J. Manuf. Sci. Eng. May 2021, 143(5): 054501.
Paper No: MANU-20-1137
https://doi.org/10.1115/1.4048636
Published Online: November 11, 2020
View Article titled, Tool Life Stage Prediction in Micro-Milling From Force Signal Analysis Using Machine Learning Methods
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Topics: Condition monitoring, Cutting, Machine learning, Machining, Micromilling, Model development, Signals, Wear
Journal Articles

Audio-Based Tool Condition Monitoring in Milling of the Workpiece Material With the Hardness Variation Using Support Vector Machines and Convolutional Neural Networks

Achyuth Kothuru, Sai Prasad Nooka, Rui Liu
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Research-Article
J. Manuf. Sci. Eng. November 2018, 140(11): 111006.
Paper No: MANU-18-1416
https://doi.org/10.1115/1.4040874
Published Online: August 3, 2018
View Article titled, Audio-Based Tool Condition Monitoring in Milling of the Workpiece Material With the Hardness Variation Using Support Vector Machines and Convolutional Neural Networks
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Topics: Artificial neural networks, Condition monitoring, Signals, Support vector machines, Wear, Cutting tools, Milling
Journal Articles

A Novel Generalized Approach for Real-Time Tool Condition Monitoring

Mahmoud Hassan, Ahmad Sadek, M. H. Attia, Vincent Thomson
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Research-Article
J. Manuf. Sci. Eng. February 2018, 140(2): 021010.
Paper No: MANU-17-1215
https://doi.org/10.1115/1.4037553
Published Online: December 18, 2017
View Article titled, A Novel Generalized Approach for Real-Time Tool Condition Monitoring
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Topics: Condition monitoring, Cutting, Signals, Wear
Journal Articles

Heuristic Feature Selection for Shaving Tool Wear Classification

Yong Wang, Adam J. Brzezinski, Xianli Qiao, Jun Ni
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Research-Article
J. Manuf. Sci. Eng. April 2017, 139(4): 041001.
Paper No: MANU-16-1444
https://doi.org/10.1115/1.4034630
Published Online: October 14, 2016
View Article titled, Heuristic Feature Selection for Shaving Tool Wear Classification
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Topics: Feature selection, Wear, Accelerometers, Sensors, Feature extraction, Condition monitoring, Gears, Artificial neural networks
Journal Articles

Machine Tool Condition Monitoring Based on an Adaptive Gaussian Mixture Model

Jianbo Yu
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Research Papers
J. Manuf. Sci. Eng. June 2012, 134(3): 031004.
https://doi.org/10.1115/1.4006093
Published Online: April 25, 2012
View Article titled, Machine Tool Condition Monitoring Based on an Adaptive Gaussian Mixture Model
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Topics: Algorithms, Condition monitoring, Density, Machine tools, Probability, Sensors, Signals, Wear, Feature extraction, Machinery
Journal Articles

Commutation Sparking Image Monitoring for DC Motor

Fei Hu, Qingbo He, Jianping Wang, Zhigang Liu, Fanrang Kong
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Technical Briefs
J. Manuf. Sci. Eng. April 2012, 134(2): 024501.
https://doi.org/10.1115/1.4005796
Published Online: April 4, 2012
View Article titled, Commutation Sparking Image Monitoring for DC Motor
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Topics: Engines, Feature extraction, Image processing, Image segmentation, Motors, Fault diagnosis, Condition monitoring, Noise (Sound), Brightness (Photometry)
Journal Articles

Quality and Inspection of Machining Operations: Tool Condition Monitoring

John T. Roth, Dragan Djurdjanovic, Xiaoping Yang, Laine Mears, Thomas Kurfess
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Research Papers
J. Manuf. Sci. Eng. August 2010, 132(4): 041015.
https://doi.org/10.1115/1.4002022
Published Online: August 3, 2010
View Article titled, Quality and Inspection of Machining Operations: Tool Condition Monitoring
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Topics: Artificial neural networks, Condition monitoring, Cutting, Feature extraction, Grinding, Hardware, Milling, Sensors, Signal processing, Signals
Journal Articles

Online Degradation Assessment and Adaptive Fault Detection Using Modified Hidden Markov Model

Seungchul Lee, Lin Li, Jun Ni
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Research Papers
J. Manuf. Sci. Eng. April 2010, 132(2): 021010.
https://doi.org/10.1115/1.4001247
Published Online: April 1, 2010
View Article titled, Online Degradation Assessment and Adaptive Fault Detection Using Modified Hidden Markov Model
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Topics: Algorithms, Condition monitoring, Fault diagnosis, Flaw detection, Manufacturing industry, Probability, Signals, Statistical process control, Wear, Quality control charts
Journal Articles

Endmill Condition Monitoring and Failure Forecasting Method for Curvilinear Cuts of Nonconstant Radii

Christopher A. Suprock, John T. Roth, Larry M. Downey
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Research Papers
J. Manuf. Sci. Eng. April 2009, 131(2): 021003.
https://doi.org/10.1115/1.3075895
Published Online: February 24, 2009
View Article titled, Endmill Condition Monitoring and Failure Forecasting Method for Curvilinear Cuts of Nonconstant Radii
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Topics: Algorithms, Condition monitoring, Cutting, Failure, Life testing, Wear, Wear testing
Journal Articles

Dynamic Modeling and Monitoring of Contour Crafting—An Extrusion-Based Layered Manufacturing Process

Satish Bukkapatnam, Ben Clark
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Technical Papers
J. Manuf. Sci. Eng. February 2007, 129(1): 135–142.
https://doi.org/10.1115/1.2375137
Published Online: August 16, 2006
View Article titled, Dynamic Modeling and Monitoring of Contour Crafting—An Extrusion-Based Layered Manufacturing Process
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Topics: Dynamics (Mechanics), Extruding, Flow (Dynamics), Manufacturing, Nozzles, Signals, Vibration, Machinery, Modeling, Dynamic modeling
Journal Articles

On-Line Prediction of Motor Shaft Misalignment Using Fast Fourier Transform Generated Spectra Data and Support Vector Regression

Olufemi A. Omitaomu, Myong K. Jeong, Adedeji B. Badiru, J. Wesley Hines
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Technical Briefs
J. Manuf. Sci. Eng. November 2006, 128(4): 1019–1024.
https://doi.org/10.1115/1.2194059
Published Online: February 3, 2006
View Article titled, On-Line Prediction of Motor Shaft Misalignment Using Fast Fourier Transform Generated Spectra Data and Support Vector Regression
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Topics: Condition monitoring, Engines, Fast Fourier transforms, Motors, Spectra (Spectroscopy), Support vector machines, Maintenance, Computation, Principal component analysis, Machinery
Journal Articles

Condition Monitoring Using a Latent Process Model with an Application to Sheet Metal Stamping Processes

Xiaoli Li, Professor, R. Du, Professor
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Technical Papers
J. Manuf. Sci. Eng. May 2005, 127(2): 376–385.
https://doi.org/10.1115/1.1870015
Published Online: April 25, 2005
View Article titled, Condition Monitoring Using a Latent Process Model with an Application to Sheet Metal Stamping Processes
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Topics: Condition monitoring, Metal stamping, Signals, Sheet metal
Journal Articles

Empirical Model Decomposition Based Time-Frequency Analysis for the Effective Detection of Tool Breakage

Yonghong Peng
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Technical Papers
J. Manuf. Sci. Eng. February 2006, 128(1): 154–166.
https://doi.org/10.1115/1.1948399
Published Online: September 9, 2004
View Article titled, Empirical Model Decomposition Based Time-Frequency Analysis for the Effective Detection of Tool Breakage
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Topics: Cutting, Milling, Spectra (Spectroscopy), Time-frequency analysis, Condition monitoring, Time series
Journal Articles

Degradation Assessment and Fault Modes Classification Using Logistic Regression

Jihong Yan, Jay Lee
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Technical Briefs
J. Manuf. Sci. Eng. November 2005, 127(4): 912–914.
https://doi.org/10.1115/1.1962019
Published Online: July 22, 2004
View Article titled, Degradation Assessment and Fault Modes Classification Using Logistic Regression
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Topics: Doors, Elevators, Feature extraction, Signals, Vibration, Wavelets, Maintenance, Feature selection, Failure, Failure mechanisms
Journal Articles

A Neuro-Fuzzy System for Tool Condition Monitoring in Metal Cutting

Omez S. Mesina, Reza Langari
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Technical Papers
J. Manuf. Sci. Eng. May 2001, 123(2): 312–318.
https://doi.org/10.1115/1.1363599
Published Online: April 1, 2000
View Article titled, A Neuro-Fuzzy System for Tool Condition Monitoring in Metal Cutting
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Topics: Artificial neural networks, Cutting, Fuzzy logic, Fuzzy neural nets, Sensors, Wear, Condition monitoring, Algorithms, Machining, Density
Journal Articles

A New Method for Real-Time Tool Condition Monitoring in Transfer Machining Stations

Ya Wu, Philippe Escande, R. Du
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Technical Papers
J. Manuf. Sci. Eng. May 2001, 123(2): 339–347.
https://doi.org/10.1115/1.1334859
Published Online: February 1, 2000
View Article titled, A New Method for Real-Time Tool Condition Monitoring in Transfer Machining Stations
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Topics: Condition monitoring, Machining, Signals, Wavelets, Wavelet transforms, Drilling