Инженерное обеспечение управления качеством в высокотехнологичных производственных системах с использованием методов статистического контроля и цифровых дво

Abstract

The article examines an engineering concept of quality management in high-tech manufacturing systems of construction structures, based on the integration of statistical process control and digital twins under Industry 4.0 conditions. It is shown that discrete acceptance control schemes are insufficient under non-stationarity and multifactorial technological regimes, whereas continuous data acquisition from IIoT sensors and their integration with CAD/BIM and SCADA make it possible to form a dynamic virtual copy of the process suitable for forecasting and automatic correction of forming and heat-and-moisture treatment parameters. Using the example of serial production of high-strength fiber-reinforced concrete panels, the transition from late strength criteria to indicators of early structure formation and geometric stability, sensitive to equipment drift and raw material variations, is substantiated. Statistical effects of an active feedback loop are presented: reduction of mean geometric deviation and variance, symmetrization of error distributions, and an increase in kurtosis as a sign of suppression of random disturbances. Nonlinear extreme dependencies of mechanical characteristics on temperature regimes are identified and interpreted through microstructural damage under overheating. The resource efficiency of adaptive control is demonstrated (reduction of cement consumption and energy costs, sharp decrease in defects) as well as high prognostic agreement of the digital twin with accelerated climatic tests up to the region of accumulation of stochastic damage, which confirms the applicability of the approach for predictive assessment of durability and production reliability.