The article discusses the development of an algorithm for automated control and adjustment of technological parameters in the production of asphalt concrete mixtures. The proposed approach is based on the analysis of data on the physical and mechanical properties of mixture components using machine learning methods and statistical analysis. The study includes analysis of existing quality control systems, development of a mathematical model for predicting the properties of the finished mixture, creation of an algorithm for optimizing technological parameters, and conducting experimental studies. The results show the possibility of improving product quality by 15-20% and reducing material consumption by 8-12% when implementing the proposed algorithm. Practical application of the development allows ensuring technological process stability and compliance of the finished product with regulatory requirements.

Keywords: asphalt concrete, pavement quality, data analysis, technological process, components, quality management, modern technologies, and automation