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Creation of a chemical-technological system digital twin using the Python language

Currently, when modeling complex technological processes in cyber-physical systems, procedures for creating so-called "digital twins" (DT) have become widespread. DT are virtual copies of real objects which reflect their main properties at various stages of the life cycle. The use of digital twins allows real-time monitoring of the current state of the simulated system, and also provides additional opportunities for engineering and deeper customization of its components to improve the quality of products. The development of the "digital twin" technology is facilitated by the ongoing Fourth Industrial Revolution, which is characterized by the massive introduction of cyber-physical systems into production process. These systems are based on the use of the latest technologies for data processing and presentation and have a complex structure of information chain between its components. When creating digital twins of such systems elements, it is advisable to use programming languages, that allow visualization of simulated processes and provide a convenient and developed apparatus for working with complex mathematical dependencies. The Python programming language has similar characteristics. In the article, as an example of a cyber- physical system, a chemical-technological system based on a horizontal-grate machine is considered. This system is designed to implement the process of producing pellets from the apatite-nepheline ore mining wastes. The article describes various aspects of creating a digital twin of its elements that carry out the chemical-technological drying process in relation to a single pellet. The digital twin is implemented using the Python 3.7.5 programming language and provides the visualization of the process in the form of a three-dimensional interactive model. Visualization is done using the VPython library. The description of the digital twin software operation algorithm is given, as well as the type of the information system interface, the input and output information type, the results of modeling the investigated chemical-technological process. It is shown that the developed digital twin can be used in three versions: independently (Digital Twin Prototype), as an instance of a digital twin (Digital Twin Instance), and also as part of a digital twins set (Digital Twin Aggregate). Read more...

Fuzzy dynamic ontological model for decision support of energy-intensive systems management based on precedents

The article discusses the features of applying the precedent approach when managing complex energy-intensive systems in the context of the need to take into account various energy, technical, environmental and operational indicators, as well as the uncertainty of many internal and external factors influence. This leads to the presence of a large amount of semi-structured information that can be presented using various scales, which determines the prospects of using the precedent approach. The proposed fuzzy ontological model for supporting decision support based on precedents is described, characterized by the use of dynamic concepts, as well as concepts in the form of different scale numerical and linguistic variables. An algorithm for assessing the proximity of precedents based on an ontological model is proposed, which differs by taking into account the dynamic aspects of changes in the state of controlled systems. The developed algorithms for fuzzy inference for decision support based on precedents are presented, which allow the use of both linguistic and numerical variables as input characteristics of the fuzzy production model, as well as using various logical connections between the rules pre-requisites. The software that implements the developed model and algorithms is described. Particular attention is paid to the modified fuzzy inference component, implemented using Python 3.8.7 language tools. To implement the user interface of the specified component, the cross-platform graphic library Tkinter was used. The results of computational experiments using real data obtained during the operation of an energy-intensive system for processing fine ore raw materials, including a conveyor-type roasting machine, are presented. Minimization of specific total costs for thermal and electrical energy was considered as a criterion for the effectiveness of management decisions. The outcome obtained showed that the proposed model and software make it possible to obtain a result comparable to the one of using complex analytical dependencies, while ensuring a reduction in time and financial costs. Read more...