Remaining Useful Life (RUL) Prediction of Equipment in Production Lines Using Artificial Neural Networks [PDF]
Sensors, 2021 Predictive maintenance of production lines is important to early detect possible defects and thus identify and apply the required maintenance activities to avoid possible breakdowns.
Ziqiu Kang +2 more
doaj +10 more sources
Remaining Useful Life (RUL) Prediction Based on the Bivariant Two-Phase Nonlinear Wiener Degradation Process [PDF]
EntropyRecent advancements in science and technology have resulted in products with enhanced reliability and extended lifespans across the aerospace and related sectors.
Lijun Sun, Yuying Liang, Zaizai Yan
doaj +6 more sources
Ensemble Neural Networks for Remaining Useful Life (RUL) Prediction
PHM Society Asia-Pacific Conference, 2023 A core part of maintenance planning is a monitoring system that provides a good prognosis on health and degradation, often expressed as remaining useful life (RUL). Most of the current data-driven approaches for RUL prediction focus on single-point prediction.
Srinivasan, Ahbishek +2 more
core +5 more sources
RUL-RVE: Interpretable assessment of Remaining Useful Life [PDF]
Software Impacts, 2022 This work has been partially supported by the Ministry of Economy, Industry and Competitiveness (“Ministerio de Economía, Industria Competitividad”) from Spain /FEDER under grant PID2020-112726-RB-I00 and by Principado de Asturias, grant SV-PA-21-AYUD/2021/50994.
Nahuel Costa, Luciano Sánchez
core +5 more sources
A Novel RUL-Centric Data Augmentation Method for Predicting the Remaining Useful Life of Bearings [PDF]
MachinesMaintaining the reliability of rotating machinery in industrial environments entails significant challenges. The objective of this paper is to develop a methodology that can accurately predict the condition of rotating machinery in order to facilitate ...
Miao He, Zhonghua Li, Fangchao Hu
doaj +3 more sources
Hybrid framework for Remaining Useful Life (RUL) prediction of rolling bearing faults
ArrayRemaining Useful Life (RUL) prediction is critical for preventing catastrophic failures in industrial systems, enabling efficient maintenance scheduling and resource optimization.
Ali Saeed +6 more
doaj +3 more sources
Remaining Useful Life (RUL) Control of Controlled Systems Under Degradation [PDF]
International Journal of Robust and Nonlinear ControlABSTRACT Remaining Useful Life (RUL) is the length of time a component or system will operate before it requires repair or replacement. Although significant efforts have been made to estimate RUL accurately, controlling RUL remains challenging.
Mônica S. Félix +2 more
+5 more sources
Demonstration of a Response Time Based Remaining Useful Life (RUL) Prediction for Software Systems [PDF]
Journal of Prognostics and Health Management, 2023 Prognostic and Health Management (PHM) has been widely applied to hardware systems in the electronics and non-electronics domains but has not been explored for software. While software does not decay over time, it can degrade over release cycles. Software health management is confined to diagnostic assessments that identify problems, whereas prognostic
Islam, Ray, Sandborn, Peter
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Predictive Analysis of Remaining Useful Life (RUL) of Batteries: Review
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTThe increasing reliance on batteries for electric vehicles, renewable energy systems, and consumer electronics has necessitated advancements in predictive models for their Remaining Useful Life (RUL). This paper reviews current methodologies for RUL prediction, focusing on machine learning techniques, data-driven approaches, and hybrid models that ...
Sakshi Belkhode +5 more
openaire +3 more sources
Remaining Useful Life Estimation (RUL) For Critical Mechanical Components In Tractor [PDF]
International Journal For Multidisciplinary ResearchThe proposed framework utilizes an evolutionary mathematical approach to optimize data-related parameters for estimating the Remaining Useful Life (RUL) of critical mechanical components. By integrating advanced time window techniques and considering factors like downtime and failure occurrences, it offers a comprehensive solution for RUL prediction ...
SAHIL BHAGAT - +2 more
openaire +2 more sources