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Keywords: remaining useful life prediction
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Journal Articles

Data and Model Synergy-Driven Rolling Bearings Remaining Useful Life Prediction Approach Based on Deep Neural Network and Wiener Process

Yonghuai Zhu, Xiaoya Zhou, Jiangfeng Cheng, Zhifeng Liu, Xiaofu Zou, Qiang Cheng, Hui Xu, Yong Wang, Fei Tao
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Research Papers
J. Manuf. Sci. Eng. April 2025, 147(4): 041005.
Paper No: MANU-24-1447
https://doi.org/10.1115/1.4067092
Published Online: November 21, 2024
...: ftao@buaa.edu.cn 28 06 2024 31 10 2024 02 11 2024 21 11 2024 data and model synergy remaining useful life prediction health indicator Wiener process plant engineering and maintenance sensing monitoring and diagnostics National Natural Science Foundation...
View Article titled, Data and Model Synergy-Driven Rolling Bearings <span class="search-highlight">Remaining</span> <span class="search-highlight">Useful</span> <span class="search-highlight">Life</span> <span class="search-highlight">Prediction</span> Approach Based on Deep Neural Network and Wiener Process
Open the PDF for Data and Model Synergy-Driven Rolling Bearings <span class="search-highlight">Remaining</span> <span class="search-highlight">Useful</span> <span class="search-highlight">Life</span> <span class="search-highlight">Prediction</span> Approach Based on Deep Neural Network and Wiener Process in another window
Topics: Physics, Rolling bearings, Service life (Equipment)
Journal Articles

Failure Detection and Remaining Life Estimation for Ion Mill Etching Process Through Deep-Learning Based Multimodal Data Fusion

Anqi He, Xiaoning Jin
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Research Papers
J. Manuf. Sci. Eng. October 2019, 141(10): 101008.
Paper No: MANU-19-1269
https://doi.org/10.1115/1.4044248
Published Online: August 31, 2019
... diagnostics remaining useful life prediction classification deep learning 07 05 2019 21 05 2019 22 05 2019 17 07 2019 Email: xi.jin@northeastern.edu Email: he.an@husky.neu.edu Copyright © 2019 by ASME 2019 ASME 1087-1357/2019/141(10)/101008/8/ $25.00 ...
View Article titled, Failure Detection and Remaining Life Estimation for Ion Mill Etching Process Through Deep-Learning Based Multimodal Data Fusion
Open the PDF for Failure Detection and Remaining Life Estimation for Ion Mill Etching Process Through Deep-Learning Based Multimodal Data Fusion in another window
Topics: Etching, Failure, Sensors, Cycles, Failure mechanisms
Journal Articles

Two-Zone Proportional Hazard Model for Equipment Remaining Useful Life Prediction

Ming-Yi You, Lin Li, Guang Meng, Jun Ni
Journal: Journal of Manufacturing Science and Engineering
Publisher: ASME
Article Type: Research Papers
J. Manuf. Sci. Eng. August 2010, 132(4): 041008.
https://doi.org/10.1115/1.4001580
Published Online: July 22, 2010
... PHM is more accurate and reliable than prediction using the traditional PHM for the entire lifecycle. In practice, this improvement is crucial for real-time maintenance decision making to prevent equipment from catastrophic failures. two-zone proportional hazard model remaining useful life...
View Article titled, Two-Zone Proportional Hazard Model for Equipment <span class="search-highlight">Remaining</span> <span class="search-highlight">Useful</span> <span class="search-highlight">Life</span> <span class="search-highlight">Prediction</span>
Open the PDF for Two-Zone Proportional Hazard Model for Equipment <span class="search-highlight">Remaining</span> <span class="search-highlight">Useful</span> <span class="search-highlight">Life</span> <span class="search-highlight">Prediction</span> in another window
Topics: Failure, Hazards, Service life (Equipment), Reliability, Modeling, Parameter estimation