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Proceedings Papers

Integrated Data Processing and Model Selection in Machine Learning Framework Development to Predict Dimensional Errors in Wire Arc Additive Manufacturing (WAAM)

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Saleh Valizadeh Sotubadi, Nicholas Hendrickson, Vinh Nguyen
Proc. ASME. MSEC2024, Volume 1: Additive Manufacturing; Advanced Materials Manufacturing; Biomanufacturing; Life Cycle Engineering, V001T01A037, June 17–21, 2024
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2024-125172
https://doi.org/10.1115/MSEC2024-125172
View Paper titled, Integrated Data Processing and Model Selection in Machine Learning Framework Development to Predict Dimensional Errors in Wire Arc Additive Manufacturing (WAAM)
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Topics: Additive manufacturing, Errors, Machine learning, Wire, Regression models, Welding, Acoustics, Feature extraction, Feedback, Model development
Proceedings Papers

Review of Recent Methods and Learning Techniques in Prediction of Tool Life

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Ulfa Fairuz Izdihar, Brijesh Patel, Zih Fong Huang, Chih-Ho Yeh, Po Ting Lin
Proc. ASME. MSEC2023, Volume 2: Manufacturing Equipment and Automation; Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T09A002, June 12–16, 2023
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2023-101060
https://doi.org/10.1115/MSEC2023-101060
View Paper titled, Review of Recent Methods and Learning Techniques in Prediction of Tool Life
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Topics: Alloy steel, Chatter, Computer numerical control machine tools, Condition monitoring, Cutting, Cutting tools, Data acquisition, Drilling, Failure, Feature extraction
Proceedings Papers

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

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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
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2021-63465
https://doi.org/10.1115/MSEC2021-63465
View Paper titled, A Semi-Supervised Multiclass Anomaly Detection Approach for Partially Labeled In-Process Measurement Data
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Topics: Algorithms, Artificial intelligence, Dimensions, Feature extraction, Flaw detection, Integrated circuit fabrication, Machine learning, Principal component analysis
Proceedings Papers

Sensor Fusion and On-Line Monitoring of Friction Stir Blind Riveting for Lightweight Materials Manufacturing

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Zhe Gao, Weihong Guo, Jingjing Li
Proc. ASME. MSEC2018, Volume 3: Manufacturing Equipment and Systems, V003T02A011, June 18–22, 2018
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2018-6507
https://doi.org/10.1115/MSEC2018-6507
View Paper titled, Sensor Fusion and On-Line Monitoring of Friction Stir Blind Riveting for Lightweight Materials Manufacturing
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Topics: Friction, Manufacturing, Riveting, Sensors, Feature extraction, Joining, Process monitoring, Aluminum alloys, Carbon, Feature selection
Proceedings Papers

An Automated System for Design for Manufacturability Analysis for Die-Casting

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Sunil Kumar, Jatinder Madan
Proc. ASME. MSEC2018, Volume 4: Processes, V004T03A035, June 18–22, 2018
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2018-6510
https://doi.org/10.1115/MSEC2018-6510
View Paper titled, An Automated System for Design for Manufacturability Analysis for Die-Casting
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Topics: Design for Manufacturing, Die casting (Process), Die castings (Product), Computer-aided design, Design, Feature extraction, Manufacturing, Modeling, Teams
Proceedings Papers

Feature Selection for Helicopter Swashplate Bearing Fault Diagnosis

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Yong Wang, Lin Li
Proc. ASME. MSEC2017, Volume 3: Manufacturing Equipment and Systems, V003T04A058, June 4–8, 2017
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2017-2643
https://doi.org/10.1115/MSEC2017-2643
View Paper titled, Feature Selection for Helicopter Swashplate Bearing Fault Diagnosis
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Topics: Bearings, Fault diagnosis, Feature selection, Ball bearings, Algorithms, Condition monitoring, Feature extraction, Maintenance, Quality control, Signals
Proceedings Papers

Heuristic Feature Selection for Shaving Tool Wear Classification

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Yong Wang, Adam J. Brzezinski, Xianli Qiao, Jun Ni
Proc. ASME. MSEC2016, Volume 2: Materials; Biomanufacturing; Properties, Applications and Systems; Sustainable Manufacturing, V002T04A040, June 27–July 1, 2016
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2016-8547
https://doi.org/10.1115/MSEC2016-8547
View Paper titled, Heuristic Feature Selection for Shaving Tool Wear Classification
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Topics: Feature selection, Wear, Accelerometers, Condition monitoring, Feature extraction, Machinery, Signals
Proceedings Papers

A Study on Condition Monitoring and Diagnosis of Injection Molding Process Using Probabilistic Neural Network Method

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Dae Seong Baek, Chengjun Li, Jung Soo Nam, Cho Rok Na, Myungho Kim, Byungohk Rhee, Sangwon Lee
Proc. ASME. MSEC2014, Volume 1: Materials; Micro and Nano Technologies; Properties, Applications and Systems; Sustainable Manufacturing, V001T04A039, June 9–13, 2014
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2014-4058
https://doi.org/10.1115/MSEC2014-4058
View Paper titled, A Study on Condition Monitoring and Diagnosis of Injection Molding Process Using Probabilistic Neural Network Method
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Topics: Artificial neural networks, Condition monitoring, Injection molding, Pressure, Cavities, Signals, Nozzles, Screws, Feature extraction, Modeling
Proceedings Papers

Fault Diagnosis of Rolling Bearings Based on Multi-Scale Entropy and Ensembled Artificial Neural Network

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Fen Chen, Quan Liu, Qin Wei, Deng Ting, Yan Ting, Su Wenqin, Peng Bingjie, Lei Zhao
Proc. ASME. MSEC2014, Volume 2: Processing, V002T02A041, June 9–13, 2014
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2014-4033
https://doi.org/10.1115/MSEC2014-4033
View Paper titled, Fault Diagnosis of Rolling Bearings Based on Multi-Scale Entropy and Ensembled Artificial Neural Network
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Topics: Artificial neural networks, Entropy, Fault diagnosis, Rolling bearings, Cycles, Feature extraction, Flaw detection, Machinery, Reliability, Time series
Proceedings Papers

Feature Extraction of Rolling Bearing Fault Based on Ensemble Empirical Mode Decomposition and Correlation Dimension

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Lei Zhao, Zude Zhou, Yang Yin, Rong Chen, Quan Liu, Qin Wei
Proc. ASME. MSEC2014, Volume 2: Processing, V002T02A043, June 9–13, 2014
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2014-4070
https://doi.org/10.1115/MSEC2014-4070
View Paper titled, Feature Extraction of Rolling Bearing Fault Based on Ensemble Empirical Mode Decomposition and Correlation Dimension
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Topics: Dimensions, Feature extraction, Rolling bearings, Machinery, Noise (Sound), Signals, Algorithms, Attractors, Cycles, Fault diagnosis
Proceedings Papers

Dynamic Feature Monitoring Technique Applied to Thin Film Deposition Processes in an Industrial PECVD Tool

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Alexander Bleakie, Dragan Djurdjanovic
Proc. ASME. MSEC2011, ASME 2011 International Manufacturing Science and Engineering Conference, Volume 2, 215-224, June 13–17, 2011
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2011-50041
https://doi.org/10.1115/MSEC2011-50041
View Paper titled, Dynamic Feature Monitoring Technique Applied to Thin Film Deposition Processes in an Industrial PECVD Tool
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Topics: Plasma-enhanced chemical vapor deposition, Thin films, Feature extraction, Integrated circuit fabrication, Capacitors, Condition monitoring, Cycles, Generators, Maintenance, Microelectronic devices
Proceedings Papers

Feature-Based Tool Condition Monitoring in a Gear Shaving Application

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A. J. Brzezinski, Y. Wang, D. K. Choi, X. Qiao, J. Ni
Proc. ASME. MSEC2008, ASME 2008 International Manufacturing Science and Engineering Conference, Volume 2, 65-74, October 7–10, 2008
Publisher: American Society of Mechanical Engineers
Paper No: MSEC_ICM&P2008-72297
https://doi.org/10.1115/MSEC_ICMP2008-72297
View Paper titled, Feature-Based Tool Condition Monitoring in a Gear Shaving Application
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Topics: Condition monitoring, Gears, Wear, Artificial neural networks, Cutting tools, Data collection, Dimensions, Feature extraction, Machinery, Multilayer perceptron
Proceedings Papers

Automatic Feature Extraction for Missing Part Detection in Forging Processes

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Zhisheng Zhang, Gabrielle Tremblay, Jionghua Jin
Proc. ASME. MSEC2006, Manufacturing Science and Engineering, Parts A and B, 683-692, October 8–11, 2006
Publisher: American Society of Mechanical Engineers
Paper No: MSEC2006-21081
https://doi.org/10.1115/MSEC2006-21081
View Paper titled, Automatic Feature Extraction for Missing Part Detection in Forging Processes
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Topics: Feature extraction, Forging, Image segmentation, Principal component analysis, Probability, Robustness