Remaining Useful Life prediction and challenges: A literature review on the use of Machine Learning Methods
出版年份 2022 全文链接
标题
Remaining Useful Life prediction and challenges: A literature review on the use of Machine Learning Methods
作者
关键词
Remaining Useful Life, Artificial intelligence, Data-driven models, Machine learning, Predictive maintenance, Prediction Process Framework
出版物
JOURNAL OF MANUFACTURING SYSTEMS
Volume 63, Issue -, Pages 550-562
出版商
Elsevier BV
发表日期
2022-05-24
DOI
10.1016/j.jmsy.2022.05.010
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Data-based model maintenance in the era of industry 4.0: A methodology
- (2022) Paul-Arthur Dreyfus et al. JOURNAL OF MANUFACTURING SYSTEMS
- Remaining Useful Life (RUL) Prediction of Equipment in Production Lines Using Artificial Neural Networks
- (2021) Ziqiu Kang et al. SENSORS
- Multiscale deep bidirectional gated recurrent neural networks based prognostic method for complex non-linear degradation systems
- (2021) Sourajit Behera et al. INFORMATION SCIENCES
- Meta deep learning based rotating machinery health prognostics toward few-shot prognostics
- (2021) Peng Ding et al. APPLIED SOFT COMPUTING
- Temporal convolutional network with soft thresholding and attention mechanism for machinery prognostics
- (2021) Yiwei Wang et al. JOURNAL OF MANUFACTURING SYSTEMS
- Zero-defect manufacturing the approach for higher manufacturing sustainability in the era of industry 4.0: a position paper
- (2021) Foivos Psarommatis et al. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
- A Data-Independent Genetic Algorithm Framework for Fault-Type Classification and Remaining Useful Life Prediction
- (2020) Hung-Cuong Trinh et al. Applied Sciences-Basel
- A survey of surveys on the use of visualization for interpreting machine learning models
- (2020) Angelos Chatzimparmpas et al. Information Visualization
- A new data-driven transferable remaining useful life prediction approach for bearing under different working conditions
- (2020) Jun Zhu et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Prediction of bearing failures by the analysis of the time series
- (2020) Abdenour Soualhi et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Data-driven prognostics of rolling element bearings using a novel Error Based Evolving Takagi-Sugeno Fuzzy Model
- (2020) Murilo Osorio Camargos et al. APPLIED SOFT COMPUTING
- A Deep Learning-Based Remaining Useful Life Prediction Approach for Bearings
- (2020) Cheng Cheng et al. IEEE-ASME TRANSACTIONS ON MECHATRONICS
- Anomaly monitoring improves remaining useful life estimation of industrial machinery
- (2020) Gurkan Aydemir et al. JOURNAL OF MANUFACTURING SYSTEMS
- Data alignments in machinery remaining useful life prediction using deep adversarial neural networks
- (2020) Xiang Li et al. KNOWLEDGE-BASED SYSTEMS
- Intelligent Prognostics of Machining Tools Based on Adaptive Variational Mode Decomposition and Deep Learning Method with Attention Mechanism
- (2020) Chongdang Liu et al. NEUROCOMPUTING
- Industrial Remaining Useful Life Prediction by Partial Observation Using Deep Learning With Supervised Attention
- (2020) Xiang Li et al. IEEE-ASME TRANSACTIONS ON MECHATRONICS
- A Data-Driven Approach With Uncertainty Quantification for Predicting Future Capacities and Remaining Useful Life of Lithium-ion Battery
- (2020) Kailong Liu et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- A Data-Driven Auto-CNN-LSTM Prediction Model for Lithium-Ion Battery Remaining Useful Life
- (2020) Lei Ren et al. IEEE Transactions on Industrial Informatics
- Zero defect manufacturing: state-of-the-art review, shortcomings and future directions in research
- (2019) Foivos Psarommatis et al. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
- Gated recurrent unit based recurrent neural network for remaining useful life prediction of nonlinear deterioration process
- (2019) Jinglong Chen et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
- Data-driven remaining useful life prediction via multiple sensor signals and deep long short-term memory neural network
- (2019) Jun Wu et al. ISA TRANSACTIONS
- Machine Learning Interpretability: A Survey on Methods and Metrics
- (2019) Diogo V. Carvalho et al. Electronics
- A Bidirectional LSTM Prognostics Method Under Multiple Operational Conditions
- (2019) Cheng-Geng Huang et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- A recurrent neural network approach for remaining useful life prediction utilizing a novel trend features construction method
- (2019) Sen Zhao et al. MEASUREMENT
- Convolution and Long Short-Term Memory Hybrid Deep Neural Networks for Remaining Useful Life Prognostics
- (2019) Zhengmin Kong et al. Applied Sciences-Basel
- A predictive model for the maintenance of industrial machinery in the context of industry 4.0
- (2019) Jose-Raul Ruiz-Sarmiento et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- Deep separable convolutional network for remaining useful life prediction of machinery
- (2019) Biao Wang et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Predicting Remaining Useful Life of Rolling Bearings Based on Deep Feature Representation and Transfer Learning
- (2019) Wentao Mao et al. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
- Estimation of Bearing Remaining Useful Life based on Multiscale Convolutional Neural Network
- (2018) Jun Zhu et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- Using Deep Learning-Based Approach to Predict Remaining Useful Life of Rotating Components
- (2018) Jason Deutsch et al. IEEE Transactions on Systems Man Cybernetics-Systems
- A Novel Image Feature for the Remaining Useful Lifetime Prediction of Bearings Based on Continuous Wavelet Transform and Convolutional Neural Network
- (2018) Youngji Yoo et al. Applied Sciences-Basel
- Prediction of Bearing Remaining Useful Life With Deep Convolution Neural Network
- (2018) Lei Ren et al. IEEE Access
- A Two-Stage Approach for the Remaining Useful Life Prediction of Bearings using Deep Neural Networks
- (2018) Min Xia et al. IEEE Transactions on Industrial Informatics
- Remaining Useful Life Prediction for Lithium-ion Battery: A Deep Learning Approach
- (2018) Lei Ren et al. IEEE Access
- Extreme Learning Machine Based Prognostics of Battery Life
- (2018) Roozbeh Razavi-Far et al. International Journal on Artificial Intelligence Tools
- Transfer Learning with Deep Recurrent Neural Networks for Remaining Useful Life Estimation
- (2018) Ansi Zhang et al. Applied Sciences-Basel
- Deep learning-based remaining useful life estimation of bearings using multi-scale feature extraction
- (2018) Xiang Li et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
- A Comparative Study on Machine Learning Algorithms for Smart Manufacturing: Tool Wear Prediction Using Random Forests
- (2017) Dazhong Wu et al. JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME
- The use of MD-CUMSUM and NARX neural network for anticipating the remaining useful life of bearings
- (2017) Akhand Rai et al. MEASUREMENT
- Machine learning-based methods for TTF estimation with application to APU prognostics
- (2016) Chunsheng Yang et al. APPLIED INTELLIGENCE
- Predicting the need for vehicle compressor repairs using maintenance records and logged vehicle data
- (2015) Rune Prytz et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- A summary of fault modelling and predictive health monitoring of rolling element bearings
- (2015) Idriss El-Thalji et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- A review on prognostic techniques for non-stationary and non-linear rotating systems
- (2015) Man Shan Kan et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- A New Multivariate Approach for Prognostics Based on Extreme Learning Machine and Fuzzy Clustering
- (2015) Kamran Javed et al. IEEE Transactions on Cybernetics
- Remaining useful life estimation based on nonlinear feature reduction and support vector regression
- (2013) T. Benkedjouh et al. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
- Bearing degradation process prediction based on the PCA and optimized LS-SVM model
- (2013) Shaojiang Dong et al. MEASUREMENT
- A Data-Driven Failure Prognostics Method Based on Mixture of Gaussians Hidden Markov Models
- (2012) Diego Alejandro Tobon-Mejia et al. IEEE TRANSACTIONS ON RELIABILITY
- Health diagnosis and remaining useful life prognostics of lithium-ion batteries using data-driven methods
- (2012) Adnan Nuhic et al. JOURNAL OF POWER SOURCES
- A Socially Inspired Framework for Human State Inference Using Expert Opinion Integration
- (2011) Shrey Modi et al. IEEE-ASME TRANSACTIONS ON MECHATRONICS
- A data-driven fuzzy approach for predicting the remaining useful life in dynamic failure scenarios of a nuclear system
- (2009) Enrico Zio et al. RELIABILITY ENGINEERING & SYSTEM SAFETY
- Thermal-error modeling for complex physical systems: the-state-of-arts review
- (2008) J. W. Li et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now