Control system for the process of preparation of dough based on the regression tree model - Zaiets, N.; Lutska, N.; Vlasenko, L. (Energy and Automation, 2024)
The paper develops a machine learning model for the dough preparation process control system at a bakery, which includes dough quality monitoring, control and forecasting. The control system will ensure continuous analysis of dough parameters, such as temperature, humidity, lifting force and titran acidity, which will ensure timely detection of deviations in dough quality and avoidance of production problems. In addition, it will contribute to the automation of the quality control process and ensure the stability of production processes, which will have a positive impact on the company's reputation and customer satisfaction. The study considered seven machine learning models, including three linear and four types of binary decision trees. The analysis of the best model - a regression decision tree - confirmed its effectiveness and the validity of the resulting hierarchical structure, in particular, the prediction of important dough indicators with a high degree of reliability, which indicates its potential in practical applications in production.Key words: dough, baking production, machine learning, monitoring, forecasting, decision tree