Real Time Production Status Monitoring System

Abstract

This research aims to develop a monitoring system to show production data and analyze machine status in real-time. It uses the Internet of Things (IoT) and the LoRa communication system. The researcher uses a tension sensor to receive tension variablesin the beaming process. A tension sensor connects to the LoRa sender. The first LoRa device is the one that takes data from a tension sensor and sends it to the second LoRa receiver. Then the ESP32 board sends the tension data to the database server. It uses an API to take the data into the Google Sheet database. Then, the tension data will be extracted and analyzed. The researcher assumes a hypothesis about the machine's operation from the data obtained to make a decision whether the machine is working or stops working. If the tension value is 0 for more than a specified time, the machine has stopped running. It can use data to calculate the length of time the machine has stopped running. It can also calculate the length of time the machine has been running. If the tension value is not the standard, the machine will be damaged. The Line application also sends notifications. Maintenance departments and related agencies can then hurry and fix the issues in time. Moreover, the researcher used the length of time the machine is running and the length of time the machine is stopped to calculate the MTBF, MTTR, and availability. These variable values are displayed in a report on a Looker Studio dashboard. This allows production status to be tracked and analyzed to solve problems in time.