The article discusses the extraction of solid mineral resources (SMR) from the bottom, such as ferromanganese nodules (FMN) and cobalt-manganese crusts (CMC), occurring in both offshore and deep regions of the World Ocean. For separating and lifting the water surface is used mining complex, which includes a hydraulically dragheads and intermediate capsule with atmospheric pressure introduced into the of extraction process in order to increase energy efficiency through the organization of a two-stage hydroascent, the first stage is carried out by external hydrostatic pressure. To determine the optimum depth of immersion of the intermediate capsule composed mathematical model. It is based on the sustainable hydroascent provided at the first stage transport (from the bottom to capsule), and reducing power consumption slurry pump performing the second stage transport (from the capsule to the sea surface). In determining the rational immersion depth were taken into account design features of slurry pipeline, mine geological parameters, the parameters of extracted minerals, performance of dragheads, the slurry flow parameters, such as concentration, consistency, density. Presents an example calculation and determined the optimal capsule insertion depth for offshore geological environments.

This article is devoted to the prediction of the residual life based on an estimate of the technical state of the induction motor. The proposed system allows to increase the accuracy and completeness of diagnostics by using an artificial neural network (ANN), and also identify and predict faulty states of an electrical equipment in dynamics. The results of the proposed system for estimation the technical condition are probability technical state diagrams and a quantitative evaluation of the residual life, taking into account electrical, vibrational, indirect parameters and detected defects. Based on the evaluation of the technical condition and the prediction of the residual life, a decision is made to change the control of the operating and maintenance modes of the electric motors.

Qualification of employees who operate technological processes directly influences the safety of production. However, the employees’’ qualification cannot completely exclude human factor. Today, there are many technologies that can minimize or eliminate human factor impact on production safety ensuring. The augmented reality technology is an example of this technology. Nowadays, the augmented reality technologies and industrial technologies integration process moves to a new level of development. These technologies have huge experience, which has been accumulated in a long period of time. -This new level turns available by this experience combination and integration; it brings additional profit to the enterprise and can be a basis for completely new technologies. This paper shows an example of combination of augmented reality technology and oil pumps maintenance. For researching of efficiency of augmented reality system for oil pump maintenance, the laboratory unit with Grundfos vertical electric centrifugal pump (CR15-4 A-FGJ-AE-HQQE) was used. The laboratory unit is a physical model of one of the continuous oil processes. The oil pump of this laboratory unit is object of this research. The algorithm of servicing of oil pump was developed. The test of system and algorithms were carried out with four groups of people: the first one had only instructions to use on hand, the second one only used the internal recommendations of the system, the third one used only the help of an expert, and the fourth used internal recommendations and, if necessary, contacted the expert. The results show the efficiency and actuality of augmented reality technology for maintenance of industrial equipment, especially for the equipment operated in remote Arctic conditions.