Автоматизовані лінії для переробки горіхів
Вантажиться...
Файли
Дата
Назва журналу
Номер ISSN
Назва тому
DOI
Анотація
A study of automated lines for processing nuts in the context of digitalization of agro-industrial production was
conducted. The functional structure of production complexes covering calibration, peeling, separation and packaging
operations was revealed. The experience of using optical sorters based on machine vision, control systems based on
programmable logic controllers and industrial Internet of Things technologies was highlighted. The technical and
economic advantages of automated walnut processing compared to manual labor were substantiated.
Опис
Ключові слова
УДК
Тип документа
Мова
ISSN
Бібліографічний опис
Коржовський В. А., Голубович І. С., Голубович О. С., Піонткевич О. В. Автоматизовані лінії для переробки горіхів // Матеріали Міжнародної науково-практичної інтернет-конференції «Молодь в науці: дослідження, проблеми, перспективи (МН-2026)», м. Вінниця, 22-26 червня 2026 р. Електрон. текст. дані. 2026. URI: https://conferences.vntu.edu.ua/index.php/mn/mn2026/paper/view/28780.
Схвалення
Рецензія
Доповнено
Цитується в
Список використаної літератури (10)
- Hussain S. Z., Ammatullah B., Kanojia V. et al. Design and development of technology for walnut cracking. J Food Sci Technol, 2018. Vol. 55. P. 4973-4983. https://doi.org/10.1007/s13197-018-3435-0
- Xiao Z., Wang J., Han L., Guo S., Cui Q. Application of Machine Vision System in Food Detection. Frontiers in Nutrition, 2022. Vol. 9. 7 p. https://doi.org/10.3389/fnut.2022.888245
- Han B., Su G., Zeng Y. et al. FDEM investigation on the crack propagation characteristics of walnut shell under multi-contact loadings. Frontiers in Materials, 2023. Vol. 10. 14 p. https://doi.org/10.3389/fmats.2023.1293683
- Zhou R., Zahid A., Majeed Y. et al. Advancement in artificial intelligence for on-farm fruit sorting and transportation. Frontiers in Plant Science, 2023. Vol. 14. 11 p. https://doi.org/10.3389/fpls.2023.1082860
- Hassoun A., Jagtap S., Garcia-Garcia G. et al. Food quality 4.0: From traditional approaches to digitalized automated analysis. Journal of Food Engineering, 2023. Vol. 337. https://doi.org/10.1016/j.jfoodeng.2022.111216
- Wang Z., Sun Q., Zhang B. Design and evaluation of pneumatic impact-twisting combined walnut shell-breaking mechanism. Journal of Food Process Engineering, 2022. Vol. 45. https://doi.org/10.1111/jfpe.14553
- Hasnan N. Z. N., Yusoff Y. M., Lim S. A. H., Kamarudin K. Potential of industrial internet of things (IIoT) to improve inefficiencies in food manufacturing. AIP Conf. Proc. 2907, 2023. https://doi.org/10.1063/5.0171393
- Lee I. H., Ma L. Integrating machine learning, optical sensors, and robotics for advanced food quality assessment and food processing. Food Innovation and Advances, 2025. Vol. 4(1). P. 65-72. https://doi.org/10.48130/fia-0025-0007
- Olorunfemi B. O., Nwulu N. I., Adebo O. A., Kavadias K. A. Advancements in machine visions for fruit sorting and grading: A bibliometric analysis, systematic review, and future research directions. Journal of Agriculture and Food Research, 2024. No. 16, 101154. https://doi.org/10.1016/j.jafr.2024.101154
- Huimin L. Design and Implementation of the Automatic Sorting System Based on PLC. 2023 IEEE 3rd International Conference on Power, Electronics and Computer Applications (ICPECA), 2023. PP. 113–117. https://doi.org/10.1109/ICPECA56706.2023.10075963