Implementation of Digital Twins and Big Data Analytics in Industrial Production Processes

The integration of digital twins into industrial production processes is expediently carried out in conjunction with big data analytics tools. The symbiosis of these innovations in the field of digital business process management allows reaching increased efficiency of each, as it is aimed not only at creating (modeling) a digital replica of an object but also at collecting and analyzing data on its operation to identify deviations, prevent malfunctions, and premature failures. Capturing data on the performance and operation metrics of the object (equipment, prototype of manufactured products, etc.) is also reasonable for further improvement, identifying reserves for increasing productivity in the case of equipment, and the quality of performed functions when it comes to products. The application of digital twins together with big data analytics in the activities of industrial enterprises has great prospects, primarily associated with increased labor productivity and cost reduction. This work presents a mathematical model for optimizing production processes, as well as the most commonly used digital software products for modeling and protecting digital twins.