Development Health Machine of Heavy Equipment Condition Monitoring System

Monitoring the performance of machines is crucial because any damages that occur within the machines can result in losses and additional costs for the company. Currently, there are performance monitoring systems available for specific types of machines, such as excavators and dump trucks, provided by Komatsu under the names VHMS and Komtrax. However, these systems are not available for the GD825A-2 motor grader model. This research aims to implement an loT system to monitor the real-time condition of heavy equipment, facilitating and improving the analysis of the equipment’s data. The research utilizes an experimental method by testing the loT system on heavy equipment in a real industrial environment. The system consists of sensors installed on the machines and a gateway connected to the internet. The sensor data is transmitted to the gateway and stored on a server, then analyzed and processed using machine learning algorithms to detect potential machine damage. The analysis results are displayed on a user dashboard that can be accessed online. The test results demonstrate that the loT system can accurately monitor machine conditions, help enhance operational efficiency, and reduce maintenance costs.