Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal International Journal of Informatics Engineering and Computing
Adel Sayed, Ahmed
Unknown Affiliation
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Predictive Maintenance for Al Sabiya Power Plant Using Machine Learning Algorithms Adel Sayed, Ahmed; Shalaby, Yasmeen Ali
International Journal of Informatics Engineering and Computing Vol. 2 No. 1 (2025): International Journal of Informatics Engineering and Computing
Publisher : ASTEEC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70687/ijimatic.v2i1.49

Abstract

This study develops a predictive maintenance framework for the Al Sabia steam power plant in Kuwait, employing Support Vector Machine (SVM) and K-nearest Neighbor (KNN) algorithms. This research focuses on anticipating maintenance needs based on critical operational parameters, including temperature, pressure, flow rate, operational hours, and alert signals. Experimental results indicate that SVM outperforms KNN, achieving an accuracy of 0.95 compared to 0.93 for KNN, along with superior precision, recall, and F1-score, suggesting its suitability for this application. Furthermore, an ensemble model SVM and KNN achieves an accuracy of 0.93. The adoption of this model is expected to markedly reduce downtime, improve storage quality, and enhance overall power plant reliability. Additionally, this paper provides a comparative analysis of a neural network model developed in TensorFlow and its equivalent model implemented in TensorFlow Lite. The analysis evaluates both models on three key performance metrics: accuracy, sample size, and latency. Both the TensorFlow and TensorFlow Lite models attain an accuracy of 0.95, affirming TensorFlow Lite's efficacy in facilitating high-performance machine learning on resource-constrained hardware.
Co-Authors Shalaby, Yasmeen Ali