Real-Time Monitoring Analysis and Predictive Maintenance of Industrial Machinery Based on Industry 4.0 Concept Using Iots

Abstract

The advancement and rise in complexity of industrial machines due to the continuous increase in demand for usage and volume has led to several bottlenecks that inhibit the devices’ full potential so, the need of the hour is to transform Industry 0 to Industry 4.0 which is actually the conversion of manual data in Industry 0 to digital data through the intelligent networking of machines in Industry 4.0. The goal for this project is to contribute towards Industry 4.0 through digitization of machines. The solution that the project aims to provide is the predictive analysis and real-time monitoring of machines. This solution is presented in the form of a fully functional app which shows the real time data of machines to the floor manager and operator. This data allows them to observe what task each machine is being utilized for and through the “History” option in app, they will be able to perform predictive analysis for the maintenance of machines. Our system will provide options to cater for complications arising on the shop floor and allow the floor manager to take actions on the basis of predictive analysis before machines start to malfunction. Real time progress of machines is monitored by an IoT node that transmits live current , temperature and vibration data of working machines. This transmitted data - being shown on Arduino IDE - is sent to firebase (which is highly personalized platform and easy to interface with android application) to convert it in real time values and then app(designed on android studio with kotlin as language) is interfaced with firebase that is accessible by the manager and operator as well. Implementing an IoT based industrial solution intends to help look over predictive maintenance and analytics and can assist manufacturers with checking and breaking down their data progressively and help anticipate when support is required. Thus, manufacturers can move from fix repair or replace maintenance model to predict and fix model. Connection of IOT node with machines makes them smart machines. With these "smart" machines, gathering the data is comparatively easier whereas the process which involves processing and visualizing this data is a relatively strenuous task. Our system is capable enough to: sense, store, display and identify if machine starts ill performing. Armed with these capabilities our system aims to tackle production delays in manufacturing industries as well as optimization of the most important resource i.e. time.