Study of feed granulation process based on system analysis – justification of optimization criteria
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Study of feed granulation process based on system analysis – justification of optimization criteria
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Abstract
The article analyzes the process of granulation of animal feed and identifies the main criteria for optimizing this process. In order to increase the productivity of animals, the use of balanced feed is considered important. Feed granulation technology not only replaces traditional feed, but also allows the use of industrial waste (corn, sunflower residues, etc.). This process provides animals with better digestion and high feed efficiency. The results of the study show that the protein and feed unit digested when using granulated feed are maintained at a higher level than other traditional feed types. The article analyzes the stages, structural and management parameters of this technological process, and is also modeled by various system approaches (morphological, functional, information). As an optimization criterion, indicators of process energy efficiency and grain quality are taken. The efficiency of the process is measured by the amount of energy used in the granulation line, the weight and quality of the output. The article also presents functional descriptions and equipment control mechanisms to improve the granulation process. Thus, this study offers practical solutions for the systematic analysis and optimization of the granulation process of compound feeds, and emphasizes the importance of analyzing and modeling equipment based on the aggregate system.
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References
[1] Basmaçıoğlu H.: Factors Affecting Pellet Quality in Compound Feed Production. Animal Production 45 (1), 2004, 23–30.
[2] Çelik M., Yılmaz O.: Pelletizing as a Feed Processing Technology and Its Effects on Animal Growth Performance. Turkish Journal of Agriculture and Natural Sciences 2(2), 2015, 89–95.
[3] Food and Agriculture Organization of the United Nations. (2019). FAOSTAT. Rome, Italy [https://www.fao.org/faostat/en/#data].
[4] Mammadov M. I.: Feeding animals with balanced feeds and its impact on productivity. Journal of Scientific Works of Azerbaijan State Agrarian University, 2007, 38.
[5] Mammadov M. I.: Ways to Increase the Efficiency of Pelleted Feeds. Journal of Scientific Works of Azerbaijan State Agrarian University 5(3), 2008, 45–52.
[6] McElhinney R. R.: Feed Manufacturing Technology IV. American Feed Industry Association, Arlington 1994.
[7] Mishurov N. P., Davydova S. A., Davydov A. A.: Promising Technologies for Improving the Quality of Compound Feeds. Equipment and Technologies in Animal Husbandry 3(35), 2019, 4–11.
[8] Smith J., Williams R.: Feed Pelleting Technology and Its Impact on Livestock Performance. Animal Feed Science and Technology 150(1–2), 2010, 83–91.
[9] Thomas M., van Zuilichem D. V., van der Poel A. F.: Physical Quality of Pelleted Animal Feed. Animal Feed Science and Technology 64(2–3), 1997, 173–192. DOI: https://doi.org/10.1016/S0377-8401(96)01058-9
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