The Komatsu GD825A-2 motor grader plays a vital role in mining operations, particularly in maintaining road quality to ensure efficient transportation and production. However, manual maintenance methods often lead to inaccurate monitoring, resulting in unexpected failures and increased downtime. To address this issue, implementing an IoT-based predictive maintenance system is proposed. By integrating real-time monitoring with advanced data analytics, this system enhances failure prediction, minimizes repair costs, and optimizes equipment availability.
Keywords: Predictive Maintenance, IoT, Heavy Equipment, Komatsu GD825A-5, Real-time Monitoring, Data Analytics.
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