Advances and limitations in machine learning approaches applied to remaining useful life predictions: a critical review

Author:

Qiao Xianpeng,Jauw Veronica Lestari,Seong Lim Chin,Banda Tiyamike

Publisher

Springer Science and Business Media LLC

Reference118 articles.

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2. Mobley RK (2002) An introduction to predictive maintenance, 2nd edn. Butterworth-Heinemann, Amsterdam; New York

3. Lei Y (2017) Intelligent fault diagnosis and remaining useful life prediction of rotating machinery. Butterworth-Heinemann Ltd, Xi’an Jiaotong University Press, Oxford, United Kingdom

4. Zerhouni N (2016) From prognostics and health systems management to predictive maintenance 1: monitoring and prognostics. ISTE Ltd/John Wiley and Sons Inc, Hoboken, NJ

5. Ferreira C, Gonçalves G (2022) Remaining useful life prediction and challenges: a literature review on the use of machine learning methods. J Manuf Syst 63:550–562. https://doi.org/10.1016/j.jmsy.2022.05.010

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