| Issue |
E3S Web of Conf.
Volume 458, 2023
International Scientific Conference Energy Management of Municipal Facilities and Environmental Technologies (EMMFT-2023)
|
|
|---|---|---|
| Article Number | 02002 | |
| Number of page(s) | 5 | |
| Section | Material Physics and Chemistry, Carbon Footprint of Materials | |
| DOI | https://doi.org/10.1051/e3sconf/202345802002 | |
| Published online | 07 December 2023 | |
Automatic monitoring system designed to detect defects in PET preforms
1 Reshetnev Siberian State University of Science and Technology, 660037 Krasnoyarsk, Russia
2 Bauman Moscow State Technical University, Artificial Intelligence Technology Scientific and Education Center, 105005, Moscow, Russia
3 Peter the Great St.Petersburg Polytechnic University, St.Petersburg, Russia
* Corresponding author: ilya-kleshko@mail.ru
The goal of this work is to automate the defect detection system for PET preforms production. For this purpose, it is necessary to consider the machine vision method, which has hardware and software structures that include many technical components. The software in turn includes two parts: one is used in the computer for image processing and the other for controlling the mechanical components of the system. However, this is a very expensive and time-consuming process due to the collection of large amounts of information with labeled defect samples. As shown, this technology can improve the scope, efficiency, quality and reliability of industrial inspection, which in turn leads to a number of advances in modern industry. Also, the company is able to increase its productivity, reduce the cost of defect controllers’ salaries, increase profits, and avoid creating situations in which equipment will be idle.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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