Internet of Things (IoT) for Live Monitoring and Analysis of 3D Printers

Abstract

As the Internet of Things (IoT) continues to evolve, the need arises to keep a constant eye on the integrity of IoT implementations to ensure that everything is running as it should. This is especially true in industrial sector. Machine Health Monitoring (MHM) was created. The primary goal of MHM is to ensure that all devices within an Industrial IoT (IIoT) implementation are functioning as expected at all times. For our specific usage of MHM, we are monitoring various readings from a 3D printer. We have currently implemented an array of sensors, and a live camera feed, with an accelerometer and a power meter soon to come. We have also created a web server running off of a Raspberry Pi 3 to hold our database and provide accessibility to the data. Through this setup, a user could access our storage and view up to the last 60 readings from the sensors in real time. The user can also view the live camera feed. We plan to use that range to implement fault detection with an alert system. We also look to eventually add predictive AI in an attempt to prevent faults before they occur. We believe our implementation provides a more cost-effective and scalable architecture for MHM. It also provides large amounts of customizability and adaptability due to our usage of generalized sensor data inputs and storage. The system is also self-monitoring, providing proper detection of its own internal issues.