Development of a digital twin of the hydrocarbon desulfurization unit.

In the context of the trend of continuous digitalization of the modern world, which is certainly due to the undeniable effective work with virtual productions that allow you to train personnel, or to predict the flow of the technological process. To achieve these goals, taking into account the development of process automation tools, modern computer technologies are being introduced using predictive neural networks. In addition, there is a constant combination of new digital technologies, such as the Internet of Things, not only in everyday life, but also in industry. This is all a consequence of the transition of the old QMS to a newer CMC, which requires more modern approaches for conducting technological processes and monitoring the quality of the products received throughout the production cycle. One of such approaches is the creation of digital twins (DT) of products and production. In addition, the processes occurring in a number of hydrocarbon production devices (electrolyzers, crystallizers, distillation columns, separators) are quite complex and insufficiently studied. This creates certain difficulties in the calculation of processes, their mathematical modeling and optimization. The tasks are complicated by the non-stationarity, nonlinearity, and multidimensionality of the processes occurring in the objects, with their low informativeness. Based on all of the above, it is easy to note that such productions are dangerous. [ABSTRACT FROM AUTHOR]