Remote monitoring and predictive maintenance in bottle filling process using industry 4.0 concepts

Industry 4.0 is nothing but automation with digitalization, which is the need of every industry to compete globally. It was introduced to enhance manufacturing capabilities by making technological advancements to increase client satisfaction and production efficiency. To increase the profitability and efficiency of the entire operation, new services and technologies are being developed at the manufacturing level. This work aims to explore Industry 4.0 from bottom to top i.e., field devices to the cloud. In this work, a simple bottle filling process has been developed using PLC programming language - Structured Text in B&R Automation Studio, visualized in human machine interface (HMI). The data generated in B&R Automation Studio is extracted using the OPC UA communication protocol and UaExpert Client, and a log is generated later using Python. The process is remotely monitored as well as controlled from anywhere in the world using the UaExpert Test Client. Then this data is pushed and stored in real-time in a Firebase database and it is used for remote monitoring the process through the developed mobile application by accessing the data from Firebase Database. Predictive maintenance (PdM) is also done where various Machine Learning Regression models like Simple Linear Regression, Random Forest Regression are implemented for predicting the failure of the machine and its components. This completes the whole field to cloud experience of Smart Manufacturing using Industry 4.0.