Dynamic model of automated timekeeping of the «operatorequipment-process» production system

The article proposes a dynamic model of automated timekeeping (DMAT) for the operatorequipment-process production system based on multiple linear regression. The model considers the infl uence of physiological (X), ergonomic (Y), technological (Z) factors, as well as the level of quality (Q) and reliability (R) of the operator's actions. Regression coeffi cients (βi) are determined by the least squares method, minimizing the standard deviation between the predicted and actual speed of operations. For automation, an algorithm is proposed that integrates computer vision and big data analysis methods. The algorithm provides continuous monitoring using a high-speed optical system that includes a digital video recorder. Video stream processing is based on image detection and recognition, which allows you to automatically segment operations and compare them with applicable standards and requirements. The built-in timekeeping unit monitors the execution time of operations in real time, detecting deviations and correcting calculations. The results are visualized in the form of interactive graphs, providing operational analysis and decision-making to improve productivity and product quality. DMAX minimizes the infl uence of external factors and ensures an increase in the effi ciency of the production system.