Real-Time Monitoring of Shop Floor Machines with Open Sources Technologies: A Case Study

Over the past few years, the development in the field of Internet of Things technologies, Big Data, and artificial intelligence has helped industries to digitalize the shop floor machine and enable the real-time monitoring and storing of data in the cloud. Real-time monitoring of shop floor machines plays a crucial role in manufacturing industries to maintain their machines, reduce downtime, and increase operational efficiency. This study presents a cost-effective solution for real-time monitoring of shop floor machines using open-source technologies, including Raspberry Pi as an edge computing device, Node-RED as a Gateway, and ESP-32 as a microcontroller. The proposed solution demonstrates the potential to revolutionize machine monitoring in manufacturing environments, offering preventive maintenance, and optimizing operational efficiency. The system gathers information from PLC with NODE-RED and various sensors such as SCT-13, ZMPT101B, and MPU 6050, installed on the shop floor machine. These sensors collect real-time data that reflect the health, performance, and power consumption of machines. The real-time sensor data also storing in the cloud as well as a local database for further analysis. Our research bridges the gap between edge computing and cloud-based monitoring, offering practical benefits to manufacturing industries, widespread adoption of our approach promises more efficient processes and resource utilization.