Quality control with machine vision in a smart factory environment
Martikainen, Vesa-Petteri (2022)
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2022121530236
https://urn.fi/URN:NBN:fi:amk-2022121530236
Tiivistelmä
The goal of this thesis was to program and install a machine vision-based quality control system in a smart factory at Savonia. The purpose of installing the machine vision quality control system was to add more smart features and get more data from the factory for educational purposes.
The quality control inspects the product parts for correct color and placement. This was achieved by using Python software Algorithms with machine vision hardware and communicating the result to the factory. The main library used for image processing is OpenCV. The factory program running in the PLCs was modified to accept the new station seamlessly to the standard factory rotation.
The results of the thesis are satisfactory. The programming and the installation of the system were successful, and it is currently in use at Savonia. The system has 100% accuracy when dealing with currently available color variations and has some additional features for a better user experience.
The quality control inspects the product parts for correct color and placement. This was achieved by using Python software Algorithms with machine vision hardware and communicating the result to the factory. The main library used for image processing is OpenCV. The factory program running in the PLCs was modified to accept the new station seamlessly to the standard factory rotation.
The results of the thesis are satisfactory. The programming and the installation of the system were successful, and it is currently in use at Savonia. The system has 100% accuracy when dealing with currently available color variations and has some additional features for a better user experience.