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All Journal International Journal of Mechanical, Industrial and Control Systems Engineering
Liam Taylor
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Computer Science & IT Engineering

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Development Of a Predictive Maintenance Framework For Hydraulic Systems Using IoT and Machine Learning Emily Green; Liam Taylor
International Journal of Mechanical, Industrial and Control Systems Engineering Vol. 1 No. 2 (2024): June: International Journal of Mechanical, Industrial and Control Systems Engin
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/ijmicse.v1i2.83

Abstract

This research develops a predictive maintenance framework for hydraulic systems by utilizing Internet of Things (IoT) technology and machine learning. Hydraulic systems often experience unexpected failures, causing expensive downtime and disrupting industrial operations. By installing IoT sensors, data about system performance and condition can be collected in real-time. This data is analyzed using machine learning algorithms to detect patterns and signs of possible failure. The proposed framework enables early detection of problems and provides timely maintenance recommendations, improving operational efficiency and reducing maintenance costs. Test results show that this approach can improve the reliability of the hydraulic system and extend the service life of the equipment. This research makes a significant contribution to the development of innovative, data-driven maintenance solutions for industry.
Co-Authors Emily Green