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International Journal For Multidisciplinary Research
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Predictive Maintenance for Nasa’s Turbofan Engine
Author(s) | KAMALKUMAAR V P, VEDA KEERTHI A, NAVANEETHA KANNAN A, YOGESH T, KIRUBAGARI B |
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Country | India |
Abstract | NASA's turbofan engine is a vital equipment used in its aircraft fleet. This engine is designed to provide the required thrust for various missions, from scientific research to astronaut training. However, this engine requires regular maintenance to ensure its optimal performance and safe operation. In this paper, we will find the remaining useful life of the turbofan engine by applying data science techniques and machine learning algorithms for predicting more accurate maintenance requirements. We will examine the performance metrics of different machine learning models and tune the parameters of the best model using random search. We will be deployed as an application using Streamlit. The final result of the web application is that it provides the results of the predictions done by the model as a csv file along with the model loss and accuracy. |
Keywords | Predictive maintenance, Remaining useful life, Machine Learning, Streamlit, Web Application |
Field | Engineering |
Published In | Volume 5, Issue 3, May-June 2023 |
Published On | 2023-05-18 |
Cite This | Predictive Maintenance for Nasa’s Turbofan Engine - KAMALKUMAAR V P, VEDA KEERTHI A, NAVANEETHA KANNAN A, YOGESH T, KIRUBAGARI B - IJFMR Volume 5, Issue 3, May-June 2023. DOI 10.36948/ijfmr.2023.v05i03.3081 |
DOI | https://doi.org/10.36948/ijfmr.2023.v05i03.3081 |
Short DOI | https://doi.org/gr9r46 |
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E-ISSN 2582-2160
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IJFMR DOI prefix is
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