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Journal Articles

Indirect Tool Condition Monitoring Using Ensemble Machine Learning Techniques

Alexandra Schueller, Christopher Saldaña

J. Manuf. Sci. Eng. January 2023, 145(1): 011006.

Paper No: MANU-22-1333

DOI: https://doi.org/10.1115/1.4055822

Published Online: October 13, 2022

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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

J. Manuf. Sci. Eng. October 2022, 144(10): 100802.

Paper No: MANU-21-1529

DOI: https://doi.org/10.1115/1.4054516

Published Online: June 22, 2022

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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

J. Manuf. Sci. Eng. July 2022, 144(7): 071008.

Paper No: MANU-21-1018

DOI: https://doi.org/10.1115/1.4053155

Published Online: December 16, 2021

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Topics: Condition monitoring, Risk

Journal Articles

A Flexible Similarity-Based Algorithm for Tool Condition Monitoring

Benjamin Stuhr, Rui Liu

J. Manuf. Sci. Eng. March 2022, 144(3): 031010.

Paper No: MANU-21-1328

DOI: https://doi.org/10.1115/1.4051885

Published Online: August 19, 2021

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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

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

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

J. Manuf. Sci. Eng. November 2018, 140(11): 111006.

Paper No: MANU-18-1416

DOI: https://doi.org/10.1115/1.4040874

Published Online: August 3, 2018

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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

J. Manuf. Sci. Eng. February 2018, 140(2): 021010.

Paper No: MANU-17-1215

DOI: https://doi.org/10.1115/1.4037553

Published Online: December 18, 2017

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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

J. Manuf. Sci. Eng. April 2017, 139(4): 041001.

Paper No: MANU-16-1444

DOI: https://doi.org/10.1115/1.4034630

Published Online: October 14, 2016

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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

J. Manuf. Sci. Eng. June 2012, 134(3): 031004.

DOI: https://doi.org/10.1115/1.4006093

Published Online: April 25, 2012

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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

J. Manuf. Sci. Eng. April 2012, 134(2): 024501.

DOI: https://doi.org/10.1115/1.4005796

Published Online: April 4, 2012

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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

J. Manuf. Sci. Eng. August 2010, 132(4): 041015.

DOI: https://doi.org/10.1115/1.4002022

Published Online: August 3, 2010

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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

J. Manuf. Sci. Eng. April 2010, 132(2): 021010.

DOI: https://doi.org/10.1115/1.4001247

Published Online: April 1, 2010

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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

J. Manuf. Sci. Eng. April 2009, 131(2): 021003.

DOI: https://doi.org/10.1115/1.3075895

Published Online: February 24, 2009

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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

J. Manuf. Sci. Eng. February 2007, 129(1): 135–142.

DOI: https://doi.org/10.1115/1.2375137

Published Online: August 16, 2006

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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

J. Manuf. Sci. Eng. November 2006, 128(4): 1019–1024.

DOI: https://doi.org/10.1115/1.2194059

Published Online: February 3, 2006

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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

J. Manuf. Sci. Eng. May 2005, 127(2): 376–385.

DOI: https://doi.org/10.1115/1.1870015

Published Online: April 25, 2005

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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

J. Manuf. Sci. Eng. February 2006, 128(1): 154–166.

DOI: https://doi.org/10.1115/1.1948399

Published Online: September 9, 2004

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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

J. Manuf. Sci. Eng. November 2005, 127(4): 912–914.

DOI: https://doi.org/10.1115/1.1962019

Published Online: July 22, 2004

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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

J. Manuf. Sci. Eng. May 2001, 123(2): 312–318.

DOI: https://doi.org/10.1115/1.1363599

Published Online: April 1, 2000

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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

J. Manuf. Sci. Eng. May 2001, 123(2): 339–347.

DOI: https://doi.org/10.1115/1.1334859

Published Online: February 1, 2000

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Topics: Condition monitoring, Machining, Signals, Wavelets, Wavelet transforms, Drilling

Journal citation

NARROW

Indirect Tool Condition Monitoring Using Ensemble Machine Learning Techniques

Condition Monitoring of Machine Tool Feed Drives: A Review

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

A Flexible Similarity-Based Algorithm for Tool Condition Monitoring

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

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

A Novel Generalized Approach for Real-Time Tool Condition Monitoring

Heuristic Feature Selection for Shaving Tool Wear Classification

Machine Tool Condition Monitoring Based on an Adaptive Gaussian Mixture Model

Commutation Sparking Image Monitoring for DC Motor

Quality and Inspection of Machining Operations: Tool Condition Monitoring

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

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

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

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

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

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

Degradation Assessment and Fault Modes Classification Using Logistic Regression

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

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

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