"ACS-Bakery: Intelligent Control Models for Bread Baking Based on Regression Analysis"
This dataset was developed within the framework of research on digital twin technologies for bakery production processes. It contains 1,000,000 records of technological process parameters collected and generated to represent various operating conditions of breadmaking systems. The dataset includes key process variables characterizing different stages of production, such as raw material properties, dough preparation parameters, fermentation conditions, baking settings, and product quality indicators. The data can be used for the development and validation of digital twin models, machine learning algorithms, predictive analytics, process optimization, and intelligent control systems in the food industry. The dataset is openly available for research and educational purposes and is intended to support studies in industrial digitalization, artificial intelligence applications, cyber-physical systems, and smart manufacturing in bakery production.