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Predicting Remaining Useful Life of Well Tubulars

Ibero-Latin American Congress on Computational Methods in Engineering (CILAMCE)
This work proposes a reliability-based framework to estimate the Remaining Useful Life (RUL) of well tubulars throughout the lifecycle of oil and gas wells. The RUL estimation is supported by a probabilistic analysis that accounts for uncertainties in geometrical and material properties, based on failure modes defined in the API/TR 5C3 standard.
null Luís Philipe Ribeiro Almeida   +6 more
openaire   +1 more source

Remaining Useful Life Prediction for Aircraft Maintenance Using Machine Learning

Quality and Reliability Engineering International
ABSTRACT Ensuring regular equipment maintenance is critical for any business that relies on machinery. Predictive maintenance (PdM) is a strategy for scheduling maintenance tasks, with a primary focus on predicting the remaining useful life (RUL) of equipment in advance.
Sana Abbes   +4 more
openaire   +2 more sources

Predicting Remaining Useful Life Using AdaBoost Algorithm

Advances in Science and Technology
Predicting the Remaining Useful Life (RUL) of machinery and critical components is crucial for proactive maintenance and operational efficiency in industrial settings. This paper presents an approach to RUL prediction using the AdaBoost algorithm, a technique that iteratively improves prediction accuracy by focusing on difficult-to-predict cases.
openaire   +1 more source

Predictive Maintenance - Exploring strategies for Remaining Useful Life (RUL) prediction

2022 IEEE 18th International Conference on Intelligent Computer Communication and Processing (ICCP), 2022
Eliza Maria Olariu   +3 more
openaire   +1 more source

Uncertainty in Remaining Useful Life Prediction

23rd ABCM International Congress of Mechanical Engineering, 2015
null Stephen Ekwaro-Osire   +3 more
openaire   +1 more source

The prediction intervals of remaining useful life based on constant stress accelerated life test data

European Journal of Operational Research, 2022
Bingxing Wang, Chao Ma, Shuidan Qin
exaly  

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