Development of a New Machine Learning-based Informatics System for Product Health Monitoring-Reference-Cited by-同舟云学术

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Development of a New Machine Learning-based Informatics System for Product Health Monitoring

Published:2020 Issue: Volume:93 Page:473-478
ISSN:2212-8271
Container-title:Procedia CIRP
language:en
Short-container-title:Procedia CIRP

Author:

Papananias Moschos,Obajemu Olusayo,McLeay Thomas E,Mahfouf Mahdi,Kadirkamanathan Visakan

Publisher

Elsevier BV

Subject

General Medicine

Reference29 articles.

1. Smart manufacturing: past research, present findings, and future directions;Kang;Int J Prec Eng Man Gr Tech,2016

2. Machine learning: a probabilistic perspective;Murphy,2012

3. Machine learning in manufacturing: advantages, challenges, and applications;Wuest;Prod Manuf Res,2016

4. McLeay TE. Unsupervised Monitoring of Machining Processes. PhD Thesis. University of Sheffield; 2016.

5. Semi-supervised learning;Zhou;Academic Press Library in Signal Processing,2014

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3. A probabilistic framework for product health monitoring in multistage manufacturing using Unsupervised Artificial Neural Networks and Gaussian Processes;Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture;2022-12-21

4. A Bayesian information fusion approach for end product quality estimation using machine learning and on-machine probing;Journal of Manufacturing Processes;2022-04

5. Data-based quality analysis in machining production: Influence of data pre-processing on the results of machine learning models;Procedia CIRP;2021

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