@inproceedings{9b911276cd7c4f56903aefac2f7aed10,
title = "Enhancing convolutional neural network deep learning for remaining useful life estimation in smart factory applications",
abstract = "Estimating the remaining useful life (RUL) of machines or components is essential for prognostics and health management (PHM) in smart factories. This paper enhances the convolutional neural network (CNN) deep learning for RUL estimation in smart factory applications. The enhanced CNN deep learning is applied to NASA C-MAPSS (Commercial Modular Aero-Propulsion System Simulation) data set to estimate the RUL of aero-propulsion engines. It is shown to have better performance than other related methods.",
keywords = "Convolutional neural network, Deep learning, Remaining useful life, Smart factory",
author = "Jiang, {Jehn Ruey} and Kuo, {Chang Kuei}",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Information, Communication and Engineering, ICICE 2017 ; Conference date: 17-11-2017 Through 20-11-2017",
year = "2018",
month = oct,
day = "1",
doi = "10.1109/ICICE.2017.8478928",
language = "???core.languages.en_GB???",
series = "Proceedings of the 2017 IEEE International Conference on Information, Communication and Engineering: Information and Innovation for Modern Technology, ICICE 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "120--123",
editor = "Lam, {Artde Donald Kin-Tak} and Prior, {Stephen D.} and Teen-Hang Meen",
booktitle = "Proceedings of the 2017 IEEE International Conference on Information, Communication and Engineering",
}