Remaining Useful Life Prediction

Remaining Useful Life (RUL) prediction aims to accurately estimate the time until a system fails, enabling proactive maintenance and preventing costly downtime. Current research heavily emphasizes leveraging advanced machine learning techniques, including graph neural networks to capture complex system relationships, physics-informed machine learning to incorporate domain knowledge, and large language models and ensemble methods to improve prediction accuracy and robustness across diverse operating conditions. These advancements are significantly impacting industries by optimizing maintenance schedules, enhancing safety, and improving overall system efficiency.

Papers

November 1, 2024

A Multi-Granularity Supervised Contrastive Framework for Remaining Useful Life Prediction of Aero-engines
Zixuan He, Ziqian Kong, Zhengyu Chen, Yuling Zhan, Zijun Que, Zhengguo Xu
Long Short Term Memory Feature Space Multi Granularity Contrastive Method Useful Life Remaining Useful Turbofan Engine Remaining Useful Life Prediction

October 4, 2024

Remaining Useful Life Prediction: A Study on Multidimensional Industrial Signal Processing and Efficient Transfer Learning Based on Large Language Models
Yan Chen, Cheng Liu
Large Language Model Study Feature Useful Life Efficient Transfer Learning Industrial Machine Learning Remaining Useful Multivariate Signal Remaining Useful Life Prediction Regression Framework

September 29, 2024

A Survey on Graph Neural Networks for Remaining Useful Life Prediction: Methodologies, Evaluation and Future Trends
Yucheng Wang, Min Wu, Xiaoli Li, Lihua Xie, Zhenghua Chen
Graph Neural Network Global Evaluation NCD Method Prognostic Prediction Useful Life Future Trend Remaining Useful Remaining Useful Life Prediction

June 21, 2024

Physics Informed Machine Learning (PIML) methods for estimating the remaining useful lifetime (RUL) of aircraft engines
Sriram Nagaraj, Truman Hickok
Machine Learning Physic Informed Machine Learning Remaining Useful Turbofan Engine Remaining Useful Life Prediction

April 7, 2024

Mixup Domain Adaptations for Dynamic Remaining Useful Life Predictions
Muhammad Tanzil Furqon, Mahardhika Pratama, Lin Liu, Habibullah, Kutluyil Dogancay
Mixup Method Useful Life Graph Mixup Domain Mixup Remaining Useful Life Prediction

March 27, 2024

IIP-Mixer:Intra-Inter Patch Mixing Architecture for Battery Remaining Useful Life Prediction
Guangzai Ye, Li Feng, Jianlan Guo, Yuqiang Chen
Lithium Ion Battery Useful Life MLP Mixer Simple Alternating Mixer Battery Management System Remaining Useful Life Prediction

January 29, 2024

Supervised Contrastive Learning based Dual-Mixer Model for Remaining Useful Life Prediction
En Fu, Yanyan Hu, Kaixiang Peng, Yuxin Chu
Temporal Feature Supervised Contrastive Learning Useful Life Simple Alternating Mixer Remaining Useful Remaining Useful Life Prediction Spatio Temporal Feature Extraction

September 21, 2023

Ensemble Neural Networks for Remaining Useful Life (RUL) Prediction
Ahbishek Srinivasan, Juan Carlos Andresen, Anders Holst
Human Prediction Aleatoric Uncertainty High Uncertainty Value Useful Life Probabilistic Approach Ensemble Neural Network Remaining Useful Life Prediction

June 21, 2023

Automated Machine Learning for Remaining Useful Life Predictions
Marc-André Zöller, Fabian Mauthe, Peter Zeiler, Marius Lindauer, Marco F. Huber
Machine Learning Online autoML Prognostic Prediction Useful Life Remaining Useful Remaining Useful Life Prediction

August 17, 2022

LAMA-Net: Unsupervised Domain Adaptation via Latent Alignment and Manifold Learning for RUL Prediction
Manu Joseph, Varchita Lalwani
Domain Adaptation Transfer Learning Manifold Learning Prognostic Prediction Latent Alignment Remaining Useful Life Prediction

July 4, 2022

Masked Self-Supervision for Remaining Useful Lifetime Prediction in Machine Tools
Haoren Guo, Haiyue Zhu, Jiahui Wang, Vadakkepat Prahlad, Weng Khuen Ho, Tong Heng Lee
Deep Learning Model Industrial Machine Life Prediction Industrial Monitoring Remaining Useful Life Prediction Masked Unsupervised Self Training

Remaining Useful Life Prediction

Papers

A Multi-Granularity Supervised Contrastive Framework for Remaining Useful Life Prediction of Aero-engines

Remaining Useful Life Prediction: A Study on Multidimensional Industrial Signal Processing and Efficient Transfer Learning Based on Large Language Models

A Survey on Graph Neural Networks for Remaining Useful Life Prediction: Methodologies, Evaluation and Future Trends

Physics Informed Machine Learning (PIML) methods for estimating the remaining useful lifetime (RUL) of aircraft engines

Mixup Domain Adaptations for Dynamic Remaining Useful Life Predictions

IIP-Mixer:Intra-Inter Patch Mixing Architecture for Battery Remaining Useful Life Prediction

Supervised Contrastive Learning based Dual-Mixer Model for Remaining Useful Life Prediction

Ensemble Neural Networks for Remaining Useful Life (RUL) Prediction

Automated Machine Learning for Remaining Useful Life Predictions

LAMA-Net: Unsupervised Domain Adaptation via Latent Alignment and Manifold Learning for RUL Prediction

Masked Self-Supervision for Remaining Useful Lifetime Prediction in Machine Tools