The causes of failure of the tangential rotary cutter bits of the road header during stonedrift in rocks of medium strength are analyzed in the article. It was revealed that the most typical cause of failure of cutter bits is premature wear of the toolholder (body) of the cutter bit. It is well known that the most effective way to improve the wear resistance is to increase hardness. The influence of the thermomechanical treatment of the material of the cutter bit toolholder on its hardness is studied. It was established that the thermomechanical treatment of the cutter bit toolholder material results in the increase of its hardness. It was found that the increase of material hardness is proportional to the increase of material strain intensity during thermomechanical treatment. It was concluded that the use of thermomechanical treatment can lead to the increase of both the hardness and wear resistance of the cutter bit material.

According to the top-priority trends and challenges in the mineral sector, and as per the mining science strategy, it is highly critical to arrange enhanced control, prediction and safety of production objects and their functioning for the preservation of automation sustainability. Improved control of databases, regulatory bonds, management, logistics and principles of sustainable development in mining makes it possible to reduce technological deviations and accidents at large mining and processing plants. Most procedural violations and accidents in surface and underground mines occur because of the unskilled actions of process flow operators. Damage in this case can be considerable, especially as compared with the expenses connected with qualitative training and persistent development of personnel engaged with supervisory control and data acquisition for the efficient operation of SCADA-systems within the automation framework of mining and processing plants. Definition of digital systems and their interrelation with multilevel automated control can be incorrect. The review of new principles can awaken interest in the conceptual assessment of digitalization processes using such notions as: numerical models, simulator, and artificial intel-ligence. Often applied formulations and principles of a digital model are substituted without justification of functional connections. On the other hand, a digital system today can be assumed as robotic lines and other numerical models and smart technologies, for instance, machining sta-tions with numerical program control. It is necessary to define the practical significance of conceptual modifications and digital transformation regarding objects of the mineral sector, using Big Data; to understand how a digital twin can influence a changeable process situation; to provide prompt prediction; to eliminate an accident; and to preserve the physical balance in the whole production system. Such intelligent and flexible productions particularly need computer-based simulators and digital twins based on technologies of Industry 4.0–extended and virtual reality on the basis of digital twins. Digital twins allow maximal simulation of real-life activity of process flow operators. The skills acquired by personnel after such simulation training enable operators to master the optimized procedure for functioning in emergency situations in mineral mining and processing. This paper exemplifies the remote training and control of process flows, which is of concern in the current international situation.

Improving the tools and mathematical methods to diversify the portfolio of oil and gas assets in the face of limited investment, high market volatility, increasing risks and uncertainties at the current level of technology development is a very urgent task. In order to form an effective investment portfolio, the authors proposed asset diversification using cluster analysis, which implies grouping sample objects according to a set of specific features. The method under consideration involves five stages of asset valuation in order to consider those assets in a three-dimensional space, taking into account the specifics of the oil and gas business, including determination of individual asset trajectory, performing spatial approximation, calculating the clustering coefficient, ranking the resulting pairs, and directly solving the portfolio formation optimization problem. This paper provides a reasonable set of metrics for diversification of the investment portfolio based on cluster analysis: main criterion - ∆PV, additional criteria - ∆Production, ∆OPEX/toe, ∆CAPEX/toe, characterized geological, environmental, social and economic aspects. Thus, the proposed methodology provides an opportunity to identify the most attractive investment projects, thereby allowing large oil and gas companies to diversify their business with minimal risk and maximum return on invested capital.