The relevance of the problem considered in the article - automation of the dosing system for galvanic production reagents, is emphasized by the fact that ecology is one of the most important problems of our time. These reagents affect vast areas of industry, while causing harm to the environment. As a result, it is necessary to consider innovations that will minimize these harmful effects. The data of the experiment on the application of the SCADA system in the automation of dosing and optimization of the control system for the processes of cleaning, filtration and selection of reagents are presented. The Aim of the work is to present the results of the conducted research. The results may be useful both for processing enterprises and for subsequent research.

Keywords: automation, galvanic production, optimization, SCADA systems, process control

This paper considers the problem of task scheduling in manufacturing systems with multiple machines operating in parallel. Four approaches to solving this problem are proposed: pure Monte Carlo Tree Search (MCTS), a hybrid MCDDQ agent combining reinforcement learning based on Double Deep Q-Network (DDQN) and Monte Carlo Tree Search (MCTS), an improved MCDDQ-SA agent integrating the Simulated Annealing (SA) algorithm to improve the quality of solutions, and a greedy algorithm (Greedy). A model of the environment is developed that takes into account machine speeds and task durations. A comparative study of the effectiveness of methods based on the makespan (maximum completion time) and idle time metrics is conducted. The results demonstrate that MCDDQ-SA provides the best balance between scheduling quality and computational efficiency due to adaptive exploration of the solution space. Analytical tools for evaluating the dynamics of the algorithms are presented, which emphasizes their applicability to real manufacturing systems. The paper offers new perspectives for the application of hybrid methods in resource management problems.

Keywords: machine learning, Q-learning, deep neural networks, MCTS, DDQN, simulated annealing, scheduling, greedy algorithm

The article proposes an approach to creating an intelligent industrial emissions monitoring system based on the YOLO architecture and digital simulation. The work is relevant for improving the effectiveness of environmental control at industrial facilities, for example, an oil refinery. The system automatically detects and classifies smoke against a complex background (glare, fog, sky), combining real video data with synthetic images of a digital model of the site. Simulation settings and augmentation have been performed for different weather and light conditions. Experiments have shown that adding 30% synthetics to the training set increases classification accuracy, especially for subtle outliers. Recommendations on simulation parameters have been developed and the precision metric for pollution classes has been evaluated. The results confirm the effectiveness of the approach and its readiness to be implemented in automation.

Keywords: machine vision, digital simulation, emission monitoring, neural network models, pollution classification

The article discusses machine learning methods, their application areas, limitations and application possibilities. Additionally highlighted achievements in deep learning, which allow obtaining accurate results with optimal time and effort. The promising architecture of neural networks of transformers is also described in detail. As an alternative approach, it is proposed to use a generative adversarial network in the process of converting a scan into elements of a digital information model.

Keywords: scanning, point cloud, information model, construction, objects, representation, neural network, machine learning

The main tasks in optimizing the automated control system for dosing and preparation of the electrode mass are considered. The tasks set to improve the accuracy of charge dosing, as well as to speed up the dosing time, are proposed to be performed using acoustic rapid analysis. The method is based on the decomposition of the acoustic signal generated by the interaction of the moving flow of the charge mixture and the charge line. The decomposition of the signal using fast Fourier transform into spectra and the allocation of sub-spectra responsible for fractional components will increase the accuracy of dosing.

Keywords: automated control system, charge, electrode mass, acoustic signal, spectral analysis, discrete Fourier transform, fractional composition of the charge mixture

A non-stationary system of automatic speed control of a DC motor with an adaptive controller is considered. Comparative simulation modeling in Simulink of the system with and without an adapter is performed. The results of the modeling confirm the stability of the adaptive system in a larger range of change of the non-stationary parameter compared to the conventional system. At the same time, the speed and quality of transient processes are maintained at the level recommended for such systems.

Keywords: automatic control system, non-stationarity, adaptive controller, subordinate control system, electromechanical object, DC motor

The role of automation in fire protection systems of technological processes is investigated. We reviewed the evolution of these systems, evaluated modern advances in automation, and analyzed their impact on improving the effectiveness of fire protection. In addition, we drew attention to the advantages of such systems, their implementation in various industries and the prospects for further development. With the constant growth of safety requirements and the desire to reduce risks, automation of fire protection systems is becoming not just an innovation, but a necessity for the sustainable development of industrial facilities.

Keywords: modern, safety, fire hazard, automation, system, insulation, fire fighting, implementation, firefighting, protection

The paper presents the concept of an intelligent superstructure designed to combine automated vertical storage systems, mobile robots and standard control systems for both warehouse and production processes into a single complex. The proposed mathematical model describes the key aspects of product placement, robot routing, and accounting for equipment throughput. Optimization algorithms allow you to create and quickly adjust storage and relocation plans based on dynamic changes (spikes in demand, disruptions, priority orders). The simulation results confirm that the implemented system helps to reduce time and resource costs, increases throughput and ensures higher adaptability of logistics operations.

Keywords: logistics, warehouse optimization, automated vertical storage systems, mobile robots, collaborative robots, warehouse management system, production process management system, mathematical model, optimization algorithms, intelligent system

production processes during the fourth industrial revolution according to the concept of Industry 4.0. The concept of Industry 4.0 provides for the digital transformation of production using modern automated production technologies and information technologies. Such transformation accelerates the pace of production and management integration of production and reduces the costs of servicing control systems and equipment. Automated production equipment of modern enterprises should be controlled using information and communication technologies. The basic technology that ensures the exchange of information between devices and facilitates decision-making on the network is the Internet of Things. Artificial intelligence, cyber-physical systems, service orientation, high-speed communication systems and remote access are technologies that allow organizing harmonious intelligent production. Thanks to this, production will have the maximum level of automation of processes and their full control, feedback between production links and product properties, reduced costs per unit of production and improved quality. Modern automation systems are analyzed and it is indicated that in order to create flexible intelligent production environments, it is necessary to use effective models of component-based industrial automation systems with high reliability. The ways to improve the efficiency of component-based systems based on modern technologies are presented: artificial intelligence, machine learning, high-speed wireless networks, forecasting systems, monitoring and data processing in real time. The creation of effective component-based industrial automation systems will reduce the time and cost per unit of production, improve its quality and reliability of production systems.

Keywords: automation, industry 4.0, efficiency, digitalization, component-based systems

The problem of modeling the dynamics and control of a quadrotor using a cascade control system based on a proportional‐integral‐derivative controller is considered. The main subject of the study is the development and simulation of a system that ensures the stable positioning of the quadrotor in the presence of external disturbances and limitations in the dynamic characteristics of the vehicle. The object of the research is the quadrotor as an unmanned aerial vehicle, while the subject is the cascade control system comprising an outer controller responsible for correcting position errors and an inner controller that maintains the stability of the vehicle’s orientation. The aim of the study is to create a mathematical model of the quadrotor’s dynamics and to implement a cascade control algorithm capable of converting position errors into control commands for adjusting the tilt angles. The work employs methods of mathematical modeling, discrete integration of the equations of motion, and cascade control algorithms implemented in MATLAB software. The simulation results demonstrate that the proposed control system significantly reduces the discrepancy between the current position of the vehicle and the specified target point, ensuring flight stability. However, residual errors have been identified, which are associated with the approximated models of motor dynamics and limitations on the maximum tilt angle, thereby necessitating further optimization of the control algorithms. The main conclusion of the study is that the developed cascade control system represents an effective solution for improving the positioning accuracy of the quadrotor and opens prospects for further research in the control of unmanned aerial vehicles

Keywords: quadrocopter, flight dynamics, mathematical modelling, cascade control, position controller, orientation controller, control optimisation

The article considers the problem of dynamic control of a 3-connected manipulator designed for trajectory following in conditions of external dynamic disturbances. To ensure the stability of the system, an adaptive PID controller based on the methods of kinematics and dynamics of a multi-link system is proposed. The analytical conclusions of direct kinematics, the calculation of the Jacobian matrix, and the perturbation compensation algorithm are described in detail. The experimental part is presented in the form of MATLAB modeling, the results of which are illustrated by graphs of motion, error convergence, dependence of link angles and control moments, as well as comparative tables of system characteristics at various levels of disturbances.

Keywords: robotics, manipulator, adaptive PID controller, dynamic control, direct kinematics, Jacobian matrix, perturbation compensation

In this article, an analysis of the main methods for solving the linear cutting problem (LCP) with the criterion of minimizing the number of knife rearrangements is presented. The linear cutting problem in its general form represents an optimization problem that involves placing given types of material (rolls) in such a way as to minimize waste and/or maximize the use of raw materials, taking into account constraints on the number of knives, the width of the master roll, and the required orders. This article discusses a specific case of the problem with an additional condition for minimizing knives' changes and the following approaches for its solution: the exhaustive search method, which ensures finding a global optimal solution but can be extremely inefficient for problems with a large number of orders, as well as random search based on genetic and evolutionary algorithms that model natural selection processes to find good solutions. Pseudocode is provided for various methods of solving the LCP. A comparison is made in terms of algorithmic complexity, controllability of execution time, and accuracy. The random search based on genetic and evolutionary algorithms proved to be more suited for solving the LCP with the minimization of waste and knife rearrangements.

Keywords: paper production planning, linear cutting, exhaustive search, genetic algorithm, waste minimization, knife permutation minimization

Steel hoisting ropes play an important role in metallurgical equipment, ensuring reliability and efficiency of lifting operations. One of the key features of their operation is the high level of contamination typical of metallurgical operations. Metallurgical processes are often accompanied by dust, metal chips and other abrasive particles that can significantly degrade ropes, causing wear and corrosion. To maintain the efficient operation of equipment it is necessary to monitor the condition of hoisting ropes in real time, which makes the task of improving automatic systems for monitoring the condition of ropes urgent. The paper reviews the methods of optical control of defects in hoisting steel ropes, the advantages and limitations of different approaches are considered. The aim of the work is to justify the effectiveness of the authors' developed method of analyzing rope defect images using neural networks in relation to the method based on the discrete Fourier transform. It is revealed that one of the most promising in terms of technical and economic efficiency of inspection methods is the application of vision system with image processing based on convolutional neural network technology, which allows to effectively detect defects in complex and changing operating conditions, such as metallurgical and mining production, where the background of the image may be non-uniform, and the distance between the camera and the rope varies.

Keywords: lifting ropes, vision systems, optical control methods, fast Fourier transform, hidden Markov models, convolutional neural networks

Modern automated process control systems include software complexes for monitoring, dispatching, data processing, and controlling industrial equipment. The correct operation of these systems depends on the predictable and stable deployment of software components, which requires a deterministic approach to configuration management. This paper proposes a mathematical model for software configuration management in APCS, based on difference equations of discrete systems. Numerical modeling was conducted in the Octave environment, confirming the correctness of the proposed model and allowing for the analysis of the impact of control parameters on process dynamics. The obtained results can be used to optimize strategies for automated deployment of software complexes in industrial systems.

Keywords: automated control, software complexes, discrete systems, difference equations, stability, dispatching, monitoring

The article offers examples of simulated processes for creating a digital twin, a monitoring process, and a cargo transportation process. A theory is proposed for calculating a mathematical model based on Petri nets. Models for placing an order and its delivery are proposed, as well as a model of information flows using the example of developing models for the processes of transporting perishable products in a refrigerated container.

Keywords: Business process, modeling, BPMN, IDEF1, DFD, Petri nets, mathematical model, intelligent 3D model

The paper presents the results of calculating reliability indicators and analyzing the fault tolerance of the subsystem for monitoring and controlling steam pressure in the steam curtain of a tubular furnace of a diesel fuel hydrotreating technological unit. The effectiveness of reserving critical elements to improve functional safety is substantiated.

Keywords: reliability, fault tolerance, steam curtain, tubular furnace, hydrotreating, diesel fuel, redundancy, functional safety

The article discusses options for solving the problem of slowing down the operating cycle of programmable logic controllers that occurs when implementing complex algorithms. For most modern programmable logic controllers, the operating cycle directly depends on the volume of the user program. The program is executed pseudo-parallel, so the complexity of the algorithm affects the slowdown of the cycle indirectly, through an increase in the code volume. The growth of the program leads to a slowdown in the controller's response to changes in the state of the inputs. In some cases, controller developers provide programmers with options that allow them to disrupt the natural order of the operating cycle, thereby reducing the response time. The advantages and disadvantages of such methods are discussed in detail in this article. As an alternative way to reduce the controller's response time, the possibility of transferring the execution of a part of the algorithm to the operator's touch panel is considered. Modern touch panels, in addition to their main task - implementing the human-machine interface, have many additional functions, including the ability to use macros. The main functionality of macros is given and the possibility of exchanging data between the controller and the panel is demonstrated. This feature is a prerequisite for delegating some of the functions of the panel controller. The limitations and risks that arise when using this approach are discussed in detail, and situations in which it is preferable to use this method are identified.

Keywords: programmable logic controller, operator touch panel, controller operation cycle, distribution of computing resources, macros

The article provides an overview of existing technical solutions, considered from the point of view of two approaches: complete replacement of the electrolysis plant with a modern analog; replacement of only the measuring part of the system. Based on the results of a review of existing technical solutions, it was concluded that the purchase and replacement of an entire electrolysis plant or a software measuring part is economically unprofitable, and Berezovskaya GRES can implement its own SEU-20 plant management system using modern Russian-made automation software, but its own development will bring significant economic benefits. due to the lower cost compared to foreign counterparts. Для проектируемой системы управления технологическим процессом выбрано необходимое оборудование. Рассчитано время реакции системы при аварийной ситуации. Разработаны электрическая структурная и функциональная схемы автоматизации электролизной установки СЭУ-20. Разработан интерфейс АРМ оператора и произведено моделирование разработанной программы с отработкой различных ситуаций.

Keywords: electrolysis plant, import substitution, remote control, remote control, PLC programming, APM operator

The transition from scheduled maintenance and repair of equipment to maintenance based on its actual technical state requires the use of new methods of data analysis based on machine learning. Modern data collection systems such as robotic unmanned complexes allow generating large volumes of graphic data in various spectra. The increase in data volume leads to the task of automating their processing and analysis to identify defects in high-voltage equipment. This article analyzes the features of using computer vision algorithms for images of high-voltage equipment of power plants and substations in the infrared spectrum and presents a method for their analysis, which can be used to create intelligent decision support systems in the field of technical diagnostics of equipment. The proposed method uses both deterministic algorithms and machine learning. Classical computer vision algorithms are applied for preliminary data processing in order to highlight significant features, and models based on unsupervised machine learning are applied to recognize graphic images of equipment in a feature space optimized for information space. Image segmentation using a spatial clustering algorithm based on the density distribution of values ​​taking into account outliers allows detecting and grouping image fragments with statistically close distributions of line orientations. Such fragments characterize certain structural elements of the equipment. The article describes an algorithm that implements the proposed method using the example of solving the problem of detecting defects in current transformers, and presents a visualization of its intermediate steps.

Keywords: diversification of management, production diversification, financial and economic purposes of a diversification, technological purposes of ensuring flexibility of production

An optimization model has been developed for the minimum required number of employees carrying out transport security measures included in transport security units, taking into account the algorithm for distributing employees, including various groups according to individual functions performed at different security levels, as well as the likelihood of various threats to transport security.

Keywords: transport strategy, digitalization of transport security, cost optimization, transport security units, requirements for ensuring transport security

The paper discusses the use of the M/M/n mass service model to analyze the performance of cloud storage systems. Simulations are performed to identify the impact of system parameters on average latency, blocking probability, and throughput. The results demonstrate how optimizing the number of servers and service intensity can improve system performance and minimize latency. The relevance of the study is due to the need to improve the performance of cloud solutions in the context of growing data volumes and increasing load on storage systems.

Keywords: cloud storage, mass service theory, M/M/n model, Python, modeling, performance analysis

within the framework of the conducted research, the task of controlling a robot of a parallel structure was considered. This paper presents a model of a 3-RPR type flat parallel robot in the Matlab package, developed for conducting computational experiments. Implementation of two types motion trajectories have been simulated in order to determine the optimal structure of the position regulators of the drive joint used in the robot control system. Six structure of regulators were compared: three classical ones: PD, PID, PDD and three of their fractional-degree analogues: FOPD, FOPID, FOPDD. The FOMCON tool was used to model fractional-degree regulators. The best results for type 3-PPR robot were shown by a control system with a FOPID regulator, which indicates the expediency of using fractional-degree regulators to control parallel robots.

Keywords: parallel robot, inverse kinematics problem, 3-RPR robot, computational experiment, working out the trajectory of movement, control system accuracy, fractional-degree regulator, parametric optimization of the regulator, comparative modeling, FOMCON tool

This article is devoted to the issues of implementation of automated control system of regional electric networks based on intelligent technologies. The significance of the issue under consideration is expressed in the fact that along with the development of technologies and their active use, electric loads in networks where large losses of electric power occur are increasing. Some issues of increasing the efficiency of production and consumption of energy resources at the regional level are considered. The main elements of the system approach to the analysis of the automated process control system of the regional energy system (APCS RES) are described. An example of the design and implementation of a pilot project for the introduction of intelligent technologies in the electrical networks of the Chechen Republic, in particular in the electrical networks of the city of Argun, is given. The most significant entities of the regional electric power industry are considered, which determine the process of functioning of the automated process control system of the power grid, as well as those that have or are capable of having an impact on the structure and process of functioning of the automated process control system of the power grid, where the degree of influence, situations and moments of influence for all the entities given are absolutely different. The conducted methodology of forming entities represents their dependence on each other to varying degrees.

Keywords: electricity metering, electrical network, intelligent technologies, automated process control system, regional energy system, electricity tariff

This study examines the control of the cooling fan speed as an effective means of reducing emissions of volatile organic compounds during three-dimensional layer-by-layer printing. The high extrusion temperatures used in modern high-speed printers lead to emissions of harmful volatile organic compounds, which poses health risks in poorly ventilated rooms. A mathematical model has been developed to establish a quadratic relationship between the fan speed and the volumetric air flow, which directly affects the deposition of volatile organic compounds on the melt surface. The experimental setup uses relay control of the motor current and proportional-integral-differentiating speed control, ensuring rapid stabilization of the air flow with minimal overshoot. From the analysis of transient characteristics, including motor current, fan speed, airflow velocity, and power consumption, it is shown that precise control of fan speed creates stable and predictable airflow movement, significantly reducing emissions of volatile organic compounds. In addition, the results show that integrating the feedback of the volatile organic compounds sensor in real time with the control of the extrusion rate can offer an even more adaptive and effective strategy for reducing emissions. This research lays the foundation for safer and more efficient 3D printing processes with layer-by-layer deposition modeling through improved temperature and emission management.

Keywords: volatile organic compounds, three-dimensional printing, adaptive control, layer-by-layer deposition, regulation

The article introduces a methodology for verifying BIM models of capital construction facilities. This approach focuses on dynamic assessment of intersection collision weights, combining geometric analysis, statistical methods, and adaptive metric weighting. Key metrics considered include granularity, geometry errors, tessellation complexity, and fill factor. The proposed methodology utilizes Python implementation with IfcOpenShell, leveraging a multithreaded architecture to significantly reduce data processing time. Testing on 20 multidisciplinary models highlights critical problematic elements such as walls, beams, and air ducts. The results demonstrate that adaptive weight distribution effectively identifies and prioritizes potential errors, improving the accuracy and reliability of BIM models. The study's findings are crucial for enhancing design and construction processes. By accurately assessing and mitigating errors, the methodology reduces project delays, cost overruns, and safety risks. It also promotes better coordination among project stakeholders, streamlining workflows and improving project outcomes. In conclusion, the proposed methodology is a valuable tool for verifying BIM models, ensuring the integrity and quality of capital construction projects. Its application can lead to more efficient, cost-effective, and reliable construction processes, benefiting both developers and end-users.

Keywords: TIM, collisions, verification, dynamic weights, adaptive metrics, algorithms, IfcOpenShell, python, standard deviation