Deep sea solid mineral resources (SMR) of the World Ocean, such as ferromanganese nodules (FMN), cobalt-manganese crusts (CMC) and the depth polymetallic sulphides (DPS) should become an alternative source of mineral resources in the near future. Reliable and productive complexes are necessary for the implementation of deep-sea mining on an industrial scale, which will be able to develop deposit with a minimum ecosystem load. So, the main problems in technological solutions are the collection or separation of SMR at the bottom and lifting them to the surface. As a technical solution, it is proposed to use a special construction draghead device for FMN and CMC collecting and separating from the bottom. The distinctive feature of the device is a vertical axis of rotation of the drive engine and the working body, which can be represented by a faceplate or a crown, the working element with the engine are concentrically inscribed in the casing with the catcher, which enclose the loosening zone, protecting surrounding water area from the turbulent mud and separated fractions. Nodules and crusts lifting using the draghead is carried out in the form of slurry through a pipeline.

Currently in the Russian Federation there is a large number of methods for determining the economic damage from environmental pollution. They make it possible to assess the quantitative damage caused by the industry to the environment and consider the environmental pollution factor when calculating the economic performance of enterprises. In general, all methods can be reduced to three main types, whose main advantages and disadvantages, as well as applicability for adjusting the performance of enterprises, and inclusion in environmental performance assessment are discussed in this article. The authors proposed a step-by-step procedure for including the factor of negative impact on the environment in the evaluation of companies' performance. First, a preliminary consolidated assessment is made by the method of specific damage. Secondly, the economic effect is calculated by the method of generalized indirect estimates. If necessary, clarification of calculations by the method of direct calculation is carried out. When calculating production efficiency indicators, considering the nature protection activities of the enterprise, a method of accounting for the prevented damage is proposed.

This article presents a part of the industrial metaverse for electric drive system diagnostics. The advantages of using a low-code/no-code platform for electric drive systems diagnostics are demonstrated. Five diagnostic scenarios were developed, programmed, and implemented. The article demonstrates the implementation and use of the platform’s main functional blocks: a visualization block (which displays the state of electric machines in any user-friendly form—graphs, Park’s vector diagrams, or diagnostic curves); a digital twin block (which simulates various engine states); a digital twin block with an engine defect (which simulates faulty engine states); and an artificial intelligence block (which trains classification model to predict various engine states). Experiments on training the artificial intelligence block using a misalignment defect dataset are presented. The dataset was divided into six classes: engine operation with/without a defect under no load, engine operation with/without a defect under a 50% load, and engine operation with/without a defect under a 100% load. The workflow for training and using the model, the basic training approaches, and the distinguishability of the presented classes are demonstrated. The model training results are shown. The article presents a methodology for extensive testing of program functionality. The obtained results demonstrate the feasibility of implementing a low-code/no-code platform and the feasibility of solving the assigned tasks with its help, as well as the simplification and reduction in engineering solution development time.