Оптимізація технологічних систем на основі потокового моделювання
Вантажиться...
Файли
Дата
Автори
Назва журналу
Номер ISSN
Назва тому
DOI
Анотація
This article focuses on the development of optimization methods for technological processes through the
management of energy, material, and information flows. It proposes the creation of symbolic models for various
operational modes of technological equipment and methods for setting optimal parameters for each type of flow. The
main attention is directed towards the implementation of algorithms capable of precisely diagnosing the state of
technological systems and automatically adjusting their operational parameters to maximize the efficiency of production
processes. This holistic approach aims not only to increase overall productivity and improve the quality of the final
product but also to reduce operational costs through intelligent process management based on detailed data analysis.
Such an approach opens new horizons for the further development of automated control systems capable of effectively
balancing between the complex interactions of different flows and adapting to production needs in real-time. The work
emphasizes the importance of incorporating advanced technologies, such as machine learning and artificial intelligence,
into technological processes to enhance adaptability and efficiency. Significant attention is given to the development of
user interfaces that facilitate convenient setup and process control, as well as enable integration with other technological
control systems within the enterprise. The described approach demonstrates that intelligent flow management can provide
not only direct benefits for enterprise efficiency but also contribute to broader sustainable development goals,
highlighting the potential for creating state-of-the-art adaptive control systems based on a deep analysis and
understanding of technological processes.
Опис
Ключові слова
Тип документа
Мова
ISSN
Бібліографічний опис
Ковалевський С. В. Оптимізація технологічних систем на основі потокового моделювання // Матеріали LІII науково-технічної конференції підрозділів ВНТУ, Вінниця, 20-22 березня 2024 р. Електрон. текст. дані. 2024. URI: https://conferences.vntu.edu.ua/index.php/all-fmt/all-fmt-2024/paper/view/20677.
Схвалення
Рецензія
Доповнено
Цитується в
Список використаної літератури (12)
- Yussuf R. O., Asfour O. S. Applications of artificial intelligence for energy efficiency throughout the building lifecycle: An overview // Energy and Buildings. – 2024. – Vol. 305. – Art. 113903. – Режим доступу: https://doi.org/10.1016/j.enbuild.2024.113903.
- Yang J., Jiang Z., Zhu S., Zhang H. Data-driven technological life prediction of mechanical and electrical products based on Multidimensional Deep Neural Network: Functional perspective // Journal of Manufacturing Systems. – 2022. – Vol. 64. – P. 53-67. – Режим доступу: https://doi.org/10.1016/j.jmsy.2022.05.014.
- Yoruk E., Radosevic S., Fischer B. Technological profiles, upgrading and the dynamics of growth: Country-level patterns and trajectories across distinct stages of development // Research Policy. – 2023. – Vol. 52, Issue 8. – Art. 104847. – Режим доступу: https://doi.org/10.1016/j.respol.2023.104847.
- Malakizadi A., Mallipeddi D., Dadbakhsh S., M'Saoubi R., Krajnik P. Post-processing of additively manufactured metallic alloys – A review // International Journal of Machine Tools and Manufacture. – 2022. – Vol. 179. – Art. 103908. – Режим доступу: https://doi.org/10.1016/j.ijmachtools.2022.103908.
- Gunasegaram D.R., Barnard A.S., Matthews M.J., Jared B.H., Andreaco A.M., Bartsch K., Murphy A.B. Machine learningassisted in-situ adaptive strategies for the control of defects and anomalies in metal additive manufacturing // Additive Manufacturing. – 2024. – Vol. 81. – Art. 104013. – Режим доступу: https://doi.org/10.1016/j.addma.2024.104013.
- Basak S., Baumers M., Holweg M., Hague R., Tuck C. Reducing production losses in additive manufacturing using overall equipment effectiveness // Additive Manufacturing. – 2022. – Vol. 56. – Art. 102904. – Режим доступу: https://doi.org/10.1016/j.addma.2022.102904.
- Bründl P., Scheck A., Nguyen H. G., Franke J. Towards a circular economy for electrical products: A systematic literature review and research agenda for automated recycling // Robotics and Computer-Integrated Manufacturing. – 2024. – Vol. 87. – Art. 102693. – Режим доступу: https://doi.org/10.1016/j.rcim.2023.102693.
- Yucesan Y. A., Dourado A., Viana F. A.C. A survey of modeling for prognosis and health management of industrial equipment // Advanced Engineering Informatics. – 2021. – Vol. 50. – Art. 101404. – Режим доступу: https://doi.org/10.1016/j.aei.2021.101404.
- Azarnia M., Rahimiyan M., Siano P. Offering of active distribution network in real-time energy market by integrated energy management system and Volt-Var optimization // Applied Energy. – 2024. – Vol. 358. – Art. 122635. – Режим доступу: https://doi.org/10.1016/j.apenergy.2024.122635
- Möhring H.-C., Wiederkehr P., Erkorkmaz K., Kakinuma Y. Self-optimizing machining systems // CIRP Annals. – 2020. – Vol. 69, Issue 2. – P. 740-763. – Режим доступу: https://doi.org/10.1016/j.cirp.2020.05.007.