@ARTICLE{Świłło_S._Enhanced_2022,
 author={Świłło, S. and Cacko, R.},
 volume={vol. 67},
 number={No 4},
 journal={Archives of Metallurgy and Materials},
 pages={1419-1425},
 howpublished={online},
 year={2022},
 publisher={Institute of Metallurgy and Materials Science of Polish Academy of Sciences},
 publisher={Committee of Materials Engineering and Metallurgy of Polish Academy of Sciences},
 abstract={In this article, the authors focused on the widely used aluminium extrusion technology, where the die quality and durability are the essential factors. In this study, detailed solutions in the three-key area have been presented. First is applying marking technology, where a laser technique was proposed as a consistent light source of high power in a selected, narrow spectral range. In the second, an automated and reliable identification method of alphanumeric characters was investigated using an advanced machine vision system and digital image processing adopted to the industrial conditions. Third, a proposed concept of online tool management was introduced as an efficient process for properly planning the production process, cost estimation and risk assessment. In this research, the authors pay attention to the designed vision system’s speed, reliability, and mobility. This leads to the practical, industrial application of the proposed solutions, where the influence of external factors is not negligible.},
 type={Article},
 title={Enhanced of Tool Management Based on Machine Vision in the Field of Metal Forming Technology},
 URL={http://journals.pan.pl/Content/125087/PDF/AMM-2022-4-27-Swillo.pdf},
 doi={10.24425/amm.2022.141069},
 keywords={die, aluminium extrusion, tool management, machine vision, digital image processing},
}