Modelling and management principles of combined granulated feed production through information-analytical systems

Main Article Content

Mahil Mammadov

mahilmi@mail.ru

https://orcid.org/0000-0002-9384-2746
Tural Mammadli

tmammadli@gmx.de

https://orcid.org/0009-0000-6301-8150

Abstract

The production of granulated compound feed in livestock enterprises is a complex technological process that requires precise monitoring of physical and chemical parameters. Ensuring efficiency and quality in this process demands advanced modelling and management approaches. The study aims to develop a methodology for modelling compound feed production through information-analytical systems and to define the principles of process management. The research is based on a systematic review of literature studies. After applying relevance and thematic selection criteria, 16 sources were retained for the final review and included in the reference list. The methodology combines literature review, comparative analysis, and synthesis. The analysis shows that effective modelling of feed production requires hybrid applications of deterministic, statistical, neural network, and fuzzy logic approaches. Information-analytical systems must adopt a multi-level architecture covering field operations, process monitoring, production management, and business planning. Artificial intelligence technologies – particularly machine learning, deep learning, and reinforcement learning – demonstrate high efficiency in quality prediction, anomaly detection, and the development of optimal management strategies. According to the comparative synthesis of the reviewed literature, the application of information-analytical systems can reduce raw material loss by 28–35%, decrease product quality variation by 58–62%, optimize energy consumption by 18–24%, increase production productivity by 20–30%, reduce deviation from plan by 67–75%, shorten technical downtime duration by 30–40%, and decrease quality control labour expenditure by 57–60%.Conclusion. For Azerbaijan, it is recommended to design systems that account for regional raw material bases, climatic conditions, and the technical capacity of local enterprises. The study confirms that the digital transformation of the feed industry is a multifaceted challenge requiring coordinated efforts among academic institutions, industrial enterprises, and governmental bodies.

Keywords:

feed production modelling, artificial intelligence, neural networks, fuzzy logic, process optimization

Sustainable Development Goal (SDG)

  • Zero hunger
  • Industry, Innovation, Technology and Infrastructure

References

Article Details

Mammadov, M., & Mammadli, T. (2026). Modelling and management principles of combined granulated feed production through information-analytical systems. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 16(3), 14-22. https://doi.org/10.35784/iapgos.9223