Computer Vision for Monitoring of 3D Printing

This thesis deals with the automatic detection of errors that can occur during time-consuming 3D printing. It uses computer vision and artificial intelligence to achieve this. The main result is a system that uses Raspberry Pi and a connected camera to periodically record the printing process and sends the images to the user's computer for detection. On this computer, the image is analysed by a convolutional neural network model and information about found error is sent to the user via a SMTP protocol. The solution also includes a dataset with 385 images of 3D printing errors sorted by type