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Keywords: prognostics and health management
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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
https://doi.org/10.1115/MSEC2021-63465
... for the application of the proposed semi-supervised methodology in real industrial settings. anomaly detection semi-supervised learning machine learning fault detection fault classification prognostics and health management industrial artificial intelligence principal component analysis Proceedings...
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Topics: Algorithms, Artificial intelligence, Dimensions, Feature extraction, Flaw detection, Integrated circuit fabrication, Machine learning, Principal component analysis
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
https://doi.org/10.1115/MSEC2020-8360
... alarms under 3%. The industrial feasibility of this method is notable, with the results achieved with a training set 99% smaller than the supervised learning classifiers. prognostics and health management timed Petri nets programmable logic controllers industrial big data principal component...
View Paper titled, Fault Diagnosis of Timed Event Systems: An Exploration of Machine Learning Methods
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Topics: Fault diagnosis, Machine learning, Principal component analysis, Programmable controllers, Algorithms, Signals, Artificial neural networks, Failure, Integrated circuit fabrication, Manufacturing