Lifetime Prediction Using a Tribology-Aware, Deep Learning-Based Digital Twin of Ball Bearing-Like Tribosystems in Oil and Gas

Group maintenance optimization of subsea Xmas trees with stochastic dependency

(2021) Dongming Fan et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Early wear detection and its significance for condition monitoring

(2021) Ping Lu et al.   TRIBOLOGY INTERNATIONAL

Comparison of permeability predictions on cemented sandstones with physics-based and machine learning approaches

(2020) Frank Male et al.   Journal of Natural Gas Science and Engineering

Review of digital twin about concepts, technologies, and industrial applications

(2020) Mengnan Liu et al.   JOURNAL OF MANUFACTURING SYSTEMS

Digital Twin for maintenance: A literature review

(2020) Itxaro Errandonea et al.   COMPUTERS IN INDUSTRY

Prediction of CO2 absorption by physical solvents using a chemoinformatics-based machine learning model

(2019) Hao Li et al.   Environmental Chemistry Letters

A systematic literature review of machine learning methods applied to predictive maintenance

(2019) Thyago P. Carvalho et al.   COMPUTERS & INDUSTRIAL ENGINEERING

Deep heterogeneous GRU model for predictive analytics in smart manufacturing: Application to tool wear prediction

(2019) Jinjiang Wang et al.   COMPUTERS IN INDUSTRY

The use of Digital Twin for predictive maintenance in manufacturing

(2019) P. Aivaliotis et al.   INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING

Spreading Process Maps for Powder-Bed Additive Manufacturing Derived from Physics Model-Based Machine Learning

(2019) Prathamesh S. Desai et al.   Metals

Uncertainty quantification using Bayesian neural networks in classification: Application to biomedical image segmentation

(2019) Yongchan Kwon et al.   COMPUTATIONAL STATISTICS & DATA ANALYSIS

Remaining useful life estimation in prognostics using deep convolution neural networks

(2018) Xiang Li et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Failure analysis of pipeline indents using steel precision balls under subsea conditions

(2018) W.S. Gill et al.   TRIBOLOGY INTERNATIONAL

Influence of temperature on the corrosion and tribocorrosion behaviour of High-Strength Low-Alloy steels used in offshore applications

(2018) A. López-Ortega et al.   TRIBOLOGY INTERNATIONAL

Decision support methods and applications in the upstream oil and gas sector

(2018) Mahmood Shafiee et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Failure prediction using machine learning and time series in optical network

(2017) Zhilong Wang et al.   OPTICS EXPRESS

A review on time series forecasting techniques for building energy consumption

(2017) Chirag Deb et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Lubricating oil conditioning sensors for online machine health monitoring – A review

(2017) Xiaoliang Zhu et al.   TRIBOLOGY INTERNATIONAL

An Empirical Comparison of Machine Learning Models for Time Series Forecasting

(2010) Nesreen K. Ahmed et al.   Econometric Reviews