Industry 4.0 has brought new technologies and approaches that can make a major contribution to improving the performance of production and service processes. For companies using blending technologies, the integration of technology and logistics is becoming increasingly important, in addition to the optimization of process parameters, as a well-designed logistics system can greatly enhance the efficiency of technological processes. The author proposes a digital twin-based solution to enhance the efficiency of technological processes in companies using blending technology through real-time optimization of technological and logistic processes supported by a digital twin solution. The presented models and methods demonstrate that significant improvements in technological and logistic processes can be achieved through the application of the presented model using digital twin solutions

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Fu, Y., Zhu, G., Zhu, M., Xuan, F. (2022), Digital twin for integration of design-manufacturing-maintenance: An overview, Chinese Journal of Mechanical Engineering, 35(1), 80. DOI: 10.1186/s10033-022-00760-x

Shen, K., Ding, L., Wang, C.C. (2022), Development of a framework to support whole-life-cycle net-zero-carbon buildings through integration of building information modelling and digital twins, Buildings, 12(10), 1747. DOI: 10.3390/buildings12101747

Chiachío, M., Megía, M., Chiachío, J., Fernandez, J., Jalón, M.L. (2022), Structural digital twin framework: Formulation and technology integration, Automation in Construction, 140, 104333. DOI: 10.1016/j.autcon.2022.104333

Zhang, L., Feng, L., Wang, J., Lin, K. (2022), Integration of design, manufacturing, and service based on digital twin to realize intelligent manufacturing, Machines, 10(4), 275. DOI: 10.3390/machines10040275

Tancredi, G.P., Vignali, G., Bottani, E. (2022), Integration of digital twin, machine-learning and industry 4.0 tools for anomaly detection: An application to a food plant, Sensors, 22(11), 4143. DOI: 10.3390/s22114143

Abdoune, F., Nouiri, M., Cardin, O., Castagna, P. (2022), Integration of artificial intelligence in the life cycle of industrial digital twins, IFAC-PapersOnLine, 55(10), 2545-2550. DOI: 10.1016/j.ifacol.2022.10.092

Overbeck, L., Rose, A., May, M., Lanza, G. (2022), Utilization Concept for Digital Twins of Production Systems Integration into the Organization and Production Planning Processes, ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb, 117(4), 244-248. DOI: 10.1515/zwf-2022-1035

Mhenni, F., Vitolo, F., Rega, A., Plateaux, R., Hehenberger, P., Patalano, S., Choley, J.-Y. (2022), Heterogeneous models integration for safety critical mechatronic systems and related digital twin definition, Applied Sciences (Switzerland), 12(6), 2787. DOI: 10.3390/app12062787

Rogachev, A.F., Skiter, N.N., Ketko, N.V., Simonov, A.B., Makarevich, I.V. (2022), Digital twins as a tool for systemic integration of innovative digital technologies in agriculture, IOP Conference Series: Earth and Environmental Science, 1069(1), 012042. DOI: 10.1088/1755-1315/1069/1/012042

How blenders work? URL: Downloaded: 28.05.2023

Major Differences Between an MES and ERP System. URL: Downloaded: 28.05.2023

Simpson, R., Ramírez, C., Núñez, H. (2022), Digital twins: Integration of food production, storage, and distribution for efficient life cycle management, Journal of Food Process Engineering, 45(1), e13940. DOI: 10.1111/jfpe.13940

Yung-Ting, C., Yuan-Tsang, H. (2023), A real-time and ACO-based offloading algorithm in edge computing, Journal of Parallel and Distributed Computing, 179, 104703. DOI: 10.1016/j.jpdc.2023.04.004

Cheng, M., Qu, Y., Jiang, C., Zhao, C. (2022), Is cloud computing the digital solution to the future of banking?, Journal of Financial Stability, 63, 101073. DOI: 10.1016/j.jfs.2022.101073


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