Version 1
: Received: 23 July 2024 / Approved: 24 July 2024 / Online: 25 July 2024 (09:08:08 CEST)
How to cite:
Chuchot, N.; Thanakijkasem, P. Production Optimization of Premium Food Can with Distortion Printing under Waving Requirement. Preprints2024, 2024071994. https://doi.org/10.20944/preprints202407.1994.v1
Chuchot, N.; Thanakijkasem, P. Production Optimization of Premium Food Can with Distortion Printing under Waving Requirement. Preprints 2024, 2024071994. https://doi.org/10.20944/preprints202407.1994.v1
Chuchot, N.; Thanakijkasem, P. Production Optimization of Premium Food Can with Distortion Printing under Waving Requirement. Preprints2024, 2024071994. https://doi.org/10.20944/preprints202407.1994.v1
APA Style
Chuchot, N., & Thanakijkasem, P. (2024). Production Optimization of Premium Food Can with Distortion Printing under Waving Requirement. Preprints. https://doi.org/10.20944/preprints202407.1994.v1
Chicago/Turabian Style
Chuchot, N. and Purit Thanakijkasem. 2024 "Production Optimization of Premium Food Can with Distortion Printing under Waving Requirement" Preprints. https://doi.org/10.20944/preprints202407.1994.v1
Abstract
This research aims to propose a novel approach to evaluate and minimize the scrap rate in the industrial production of premium food cans with distortion printing. Beyond cost considerations, a critical aspect of modern food can manufacturing is the aesthetic quality of the graphical display. In addition to traditional formability requirements, a waving requirement is defined. Detailed real production conditions are provided and discussed. The material of interest is a double cold-reduced (DR) low-carbon steel sheet and chromium-coated tin-free steel with a thickness of 0.16 mm. These sheets are laminated on both sides with PET film before distortion printing on the exterior. A material parameter identification method is proposed and illustrated to address the challenges in characterizing such a thin sheet. The thickness profile and flange length are key criteria for this identification. Digital image correlation (DIC) and a microscope are used to measure the thickness distribution and flange length. Within the manufacturing system, uncertainties arising from material properties and forming processes can lead to scraps or defects. Finite element analysis (FEA) is adopted for process analysis and validated with experiment. Uncertainty propagation via metamodeling, employing radial basis function (RBF) neural networks, is adopted for the scrap rate evaluation. The study concludes with process optimization recommendations to reduce scrap.
Keywords
waving; scrap rate; distortion printing; food can forming; uncertainty
Subject
Engineering, Industrial and Manufacturing Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
