Abstract

Maintenance is crucial for Power Plant Company Limited to uphold efficiency in electricity production, particularly concerning the water pump's role in driving the system. Weekly data recording and analysis, especially on parameters like vibration, aid in detecting abnormalities and facilitating timely maintenance. However, manual recording poses issues such as errors from record data and risks to employees entering high-risk areas for measurements. The company integrates Industry 4.0 principles by designing an IoT-based data recording and analysis system to address this. This system comprises four layers: Layer one is the sensing layer using vibration sensor SW420 to receive a vibration value from the water pump motor. Layer two network layers using Heltec esp32 LoRa V3 to receive data from layer one and send data to the next layer, layer three data processing using MySQL and phpMyAdmin for database and analysis, and layer 4 application layers using Line Notify service to notice abnormal vibration from the water pump motor. Results indicate the system has an accuracy of 92.24% from the sensor and effective detection of abnormalities, ensuring stable operational use. Implementing this system enhances predictive and preventive maintenance capabilities, minimizes employee errors, and provides workplace safety.