The maintenance of oil pumps is a complex task for any operating organization, and for an industrial enterprise in the oil and gas sector of the economy, this issue has a high degree of urgency. One of the reasons for this is a wide spread of pumping equipment in all areas of oil and gas enterprises. At the same time, an aggressive environment, uneven load, remote facilities, and harsh climatic zones (especially in the areas of the Arctic region or production platforms) are factors that make it relevant to develop special systems that help or simplify the maintenance of pumping equipment. Dynamic modeling is one of the modern technologies which allows for solving the urgent issue of assessing the technical condition of equipment. It is the basis of systems that carry out diagnostics and prognostic calculations and allow for assessing the dynamic state of objects under various conditions of their operation, among other functions. Augmented reality technology is a technology that allows for reducing the time for equipment maintenance by reducing the time for searching and processing various information required in the maintenance process. This paper presents an investigation of the effectiveness of an augmented reality and a dynamic simulation system collaboration in oil pump maintenance. Since there is insufficient research on the joint application of these two technologies, the urgent issue is to prove the effectiveness of such collaboration. For this purpose, this paper provides a description of the system structure, gives a description of the development process of the augmented reality system application and tests the application using Microsoft HoloLens 2.

Grinding is the most energy-intensive process among all stages of raw material preparation and determines the course of subsequent ore beneficiation stages. Level of electricity consumption is determined in accordance with load characteristics forming as a result of ore destruction in the mill. Mill drum speed is one of process variables due to which it is possible to control ore destruction mechanisms when choosing speed operation mode of adjustable electric mill drive. This study on increasing energy efficiency due to using mill electric drive is based on integrated modelling of process equipment – grinding process and electromechanic equipment – electric drive of grinding process. Evaluating load torque by means of its decomposition into a spectrum, mill condition is identified by changing signs of frequency components of torque spectrum; and when studying electromagnetic torque of electric drive, grinding process is monitored. Evaluation and selection of efficient operation mode of electric drive is based on the obtained spectrum of electromagnetic torque. Research results showed that with increasing mill drum speed – increasing impact energy, load torque values are comparable for the assigned simulation parameters. From the spectra obtained, it is possible to identify mill load condition – speed and fill level. This approach allows evaluating the impact of changes in process variables of grinding process on parameters of electromechanical system. Changing speed operation mode will increase grinding productivity by reducing the time of ore grinding and will not lead to growth of energy consumption. Integration of digital models of the technological process and automated electric drive system allows forming the basis for developing integrated methods of monitoring and evaluation of energy efficiency of the entire technological chain of ore beneficiation.

The relevance of the research is due to the need to stabilize the composition of the melting products of copper-nickel sulfide raw materials in the Vanyukov furnace. The goal of this research is to identify the most suitable methods for the aggregation of the real time data for the development of a mathematical model for control of the technological process of melting copper-nickel sulfide raw materials in the Vanyukov furnace. Statistical methods of analyzing the historical data of the real technological object and the correlation analysis of process parameters are described. Factors that exert the greatest influence on the main output parameter (copper content in matte) and ensure the physical-chemical transformations are revealed. An approach to the processing of the real time data for the development of a mathematical model for control of the melting process is proposed. The stages of processing the real time information are considered. The adopted methodology for the aggregation of data suitable for the development of a control model for the technological process of melting copper-nickel sulfide raw materials in the Vanyukov furnace allows us to interpret the obtained results for their further practical application.