The Internet of Things: Real-Time Monitoring System for Production Machine

Abstract

The importance of optimization in the manufacturing industry to achieve efficiency and effectiveness, especially in production machines. This research focuses on developing a real-time monitoring system based on the internet to monitor power consumption and production machines' speed accurately. The data taken by the real-time monitoring system is integrated into the ERP System, which is stored as time series data of power consumption and engine speed. The importance of making production cost estimates, especially on the power consumption of a production machine for the future, and functioning as a tool for real-time monitoring, the data obtained is processed by regression to get an estimate of the total power consumption for several expected outputs. The data is processed using a linear regression algorithm to predict power consumption at the desired speed on the intended production machine. To get a better tool than the one that existed before, the method in its development uses PIECES analysis. In its implementation, this real-time monitoring system runs according to the objectives, and the data obtained is as expected. This model was developed on production machines in the flexible packaging industry that uses rotogravure machines. It is possible that it can be used on production machines in other industries that use electrical power correlated with the speed measured based on the rotation of a motor.