Stability Of Processes Research Articles

Bayesian stability and force modeling for uncertain machining processes

Accurately simulating machining operations requires knowledge of the cutting force model and system frequency response. However, this data is collected using specialized instruments in an ex-situ manner. Bayesian statistical methods instead learn the system parameters using cutting test data, but to date, these approaches have only considered milling stability. This paper presents a physics-based Bayesian framework which incorporates both spindle power and milling stability. Initial probabilistic descriptions of the system parameters are propagated through a set of physics functions to form probabilistic predictions about the milling process. The system parameters are then updated using automatically selected cutting tests to reduce parameter uncertainty and identify more productive cutting conditions, where spindle power measurements are used to learn the cutting force model. The framework is demonstrated through both numerical and experimental case studies. Results show that the approach accurately identifies both the system natural frequency and cutting force model.

Evidence of Preferential Aluminum Site Loss during Reaction-Induced Dealumination.

Understanding the mechanism of steam-induced dealumination of zeolite catalysts is of high relevance for tuning their performance and stability in multiple industrial processes. A combination of 27Al and 1H-1H double-quantum single-quantum magic angle spinning nuclear magnetic resonance and diffuse-reflectance ultraviolet-visible spectroscopies identified a preferential dealumination of tetrahedral aluminum sites in H-ZSM-5 zeolites. Framework aluminum atoms facing channels display reactivity toward steam higher than that of those in their intersections. Dealumination randomly occurs on isolated and proximate sites. However, the concentration of the latter sites decays more prominently. These findings contribute to a better understanding of the stability of zeolite catalysts in the presence of steam.

DETERMINATION OF THE STABILITY PERIOD OF TURNING CUTTERS FOR HEAVY MACHINE TOOLS

To determine the optimal cutting modes under conditions of increased requirements for the stability of technological processes, it is necessary to take into account the value of the tool life with a given probability. In this paper, the stability dependence for prefabricated cutters used on heavy machine tools with maximum diameters Dmax = 1250-2500 mm is specified using the group argumentation method. The study presents a new mathematical model that establishes the relationship between tool fracture resistance and key operational parameters. This model incorporates the probabilistic nature of tool performance, which allows for a more accurate assessment of the impact of part size variation, cutting conditions, and process variability. The proposed relationship facilitates the determination of cutting modes that not only increase tool stability but also ensure the reliability and efficiency of heavy machine tools in industrial environments. This mathematical dependence makes it possible to take into account the variation of workpiece parameters and cutting modes, which is especially important when working with large-sized parts on heavy-duty machine tools. The results of the study are of practical importance for industry, as they make it possible to increase the sustainability and productivity of technological processes.

Identifying periods impacted by sewer inflow and infiltration using time series anomaly detection

Accurate diagnosis of sewer inflow and infiltration (I/I) is crucial for ensuring the safe transportation of sewage and the stability of wastewater treatment processes. Identifying periods impacted by I/I is essential for I/I diagnosis, but current methods lack a standard criterion and require adaptation to specific conditions, resulting in low accuracy, complexity, and limited generalizability. This paper proposes a novel approach to distinguish I/I periods from time series of sewer measurements based on anomaly detection theory through an iterative use of a time-series reconstruction model. This method eliminates the need for external data such as rainfalls and avoids intensive manual data analysis. Operating directly on in-sewer data, it enhances accuracy compared to existing approaches and is applicable to various external factors such as rainfall, snowmelt, and seawater intrusion. The method can be applicable to a broad range of monitoring data, including flow rate, temperature, and conductivity. Validated through simulation studies and demonstrated via real-life applications, this method offers an efficient solution for I/I detection, facilitating further I/I diagnosis, including I/I quantification and location identification.

Stability Analysis of Jet Fuel-Bioethanol Blends: an Experimental Approach

Incorporating bioethanol into jet fuel blends has garnered increasing attention as a viable strategy to reduce dependence on fossil fuels and address environmental issues. This study investigates the influence of different amounts of bioethanol on the stability properties of jet fuel blends. Bioethanol addition to jet fuel causes a steady increase in its freezing point. The alteration has been attributed to the destabilizing effect caused by polar hydrogen bonds in bioethanol on the intermolecular forces. Oxidation stability analysis demonstrates a clear correlation between ethanol content and a swift decrease in pressure resistance. Although pure jet fuel is highly stable, mixes that include bioethanol show much lower stability. This decline highlights the reduced impact of bioethanol on fuel stability and oxidation processes. The simultaneous occurrence of gum formation emphasizes the need for careful formulation strategies to prevent stability problems and system complexities. Moreover, the complex influence of bioethanol on the temperature, stability, and oxidation properties of jet fuel blends highlights the importance of using accurate formulation methodologies to improve aviation fuels.

Synthesis of chitosan nanoparticles (CSNP): effect of CH-CH-TPP ratio on size and stability of NPs.

In the face of a pressing global issue-the escalating threat of antibiotic resistance-the development of new antimicrobial agents is urgent. Nanotechnology, with its innovative approach, emerges as a promising solution to enhance the efficacy of these agents and combat the challenge of microbial resistance. Chitosan nanoparticles (CSNPs) stand out in biomedical applications, particularly in the controlled release of antibiotics, with their unique properties such as biocompatibility, stability, biodegradability, non-toxicity, and simple synthesis processes suitable for sensitive molecules. This study synthesized CSNPs using the ionotropic gelation method, with tripolyphosphate (TPP) as the crosslinking agent. Various CS: TPP ratios (6:1, 5:1, 4:1, 3:1, 2:1) were tested, and the resulting nanoparticles were evaluated using dynamic light scattering (DLS). The CS: TPP ratio of 4:1, with an average hydrodynamic diameter (DHP) of (195 ± 10) nm and a zeta potential of (51 ± 1) mV, was identified as the most suitable for further analysis. The characterization of NPs by Transmission Electron Microscope (TEM) and atomic force microscopy (AFM) revealed diameters of (65 ± 14) nm and (102 ± 18) nm, respectively. Notably, CSNPs exhibited significant aggregation during centrifugation and lyophilization, leading to diameter increases of up to 285% as measured by AFM. The antibacterial activity of CSNPs against Staphylococcus aureus and Escherichia coli was assessed using the resazurin assay. It was found that CSNPs not subjected to centrifugation, freezing, and lyophilization retained their antimicrobial activity. In contrast, those that underwent these processes lost their efficacy, likely due to aggregation and destabilization of the system. This study presents a straightforward and effective protocol for encapsulating sensitive active agents and synthesizing chitosan nanoparticles, a potential system with significant implications in the fight against antibiotic resistance.

DbPTM 2025 update: comprehensive integration of PTMs and proteomic data for advanced insights into cancer research.

Post-translational modifications (PTMs) are essential for modulating protein function and influencing stability, activity and signaling processes. The dbPTM 2025 update significantly expands the database to include over 2.79 million PTM sites, of which 2.243 million are experimentally validated from 48 databases and over 80 000 research articles. This version integrates proteomic data from 13 cancer types, with a particular focus on phosphoproteomic data and kinase activity profiles, allowing the exploration of personalized phosphorylation patterns in tumor samples. Integrating kinase-substrate phosphorylations with E3 ligase-substrate interactions, dbPTM 2025 provides a detailed map of PTM regulatory networks, offering insights into cancer-specific post-translational regulations. This update also includes advanced search capabilities, enabling users to efficiently query PTM data across species, PTM typesand modified residues. The platform's new features-interactive visualization tools and streamlined data downloads-allow researchers to access and analyze PTM data easily. dbPTM 2025 also enhances functional annotations, regulatory networks and disease associations, broadening its application for cancer research and the study of disease-associated PTMs. Through these enhancements, dbPTM 2025 is a comprehensive, user-friendly resource, facilitating the study of PTMs and their roles in cancer research. The database is now freely accessible at https://biomics.lab.nycu.edu.tw/dbPTM/.

The development of carbon nanostructured biosensors for glucose detection to enhance healthcare services: a review

In this review, the forefront of biosensor development has been marked by a profound exploration of carbon nanostructured materials for the specific application of glucose detection. Moreover, this progressive line of inquiry capitalizes on the distinctive attributes of carbon nanostructured materials such as carbon nanotubes, carbon quantum dots, and graphene which exhibit unique characteristics in the development of biosensor engineering design. It also enhanced analytical performances regarding the limit of detection, selectivity, sensitivity, and reproducibility towards glucose detection in biological samples. Most importantly, the strategic integration of carbon nanostructured-based biosensor architectures has played a significant role in advancements, characterized by heightened sensitivity, exquisite selectivity, and augmented stability in glucose detection processes. Furthermore, utilizing these advanced materials has engendered a transformative impact on electrochemical properties, propelling the biosensors to achieve rapid and precise glucose-sensing capabilities. The confluence of carbon nanostructures with biosensor technology has not only elevated the scientific understanding of glucose detection mechanisms. Still, it has also paved the way for miniaturized and portable biosensors. This transformative shift holds great promise for the realization of point-of-care diagnostics, representing a pivotal step towards durability and efficient glucose monitoring in health/medical care. These advancements emphasize the crucial role of carbon nanostructured-based biosensors in opening the way to a new avenue of superiority and effectiveness in diabetes management. Conclusively, the challenges and, in a forward-looking stance, the prospective futures of glucose biosensors anchored on carbon nanostructured frameworks were considered.

Control of membrane biofouling in MBR for wastewater treatment by biohybrid membrane with superhydrophilic self-QQ function

Quorum quenching (QQ) is an effective method for controlling MBR (membrane bioreactor) membrane biofouling by regulating the release of autoinducer during the quorum sensing (QS) process. However, the addition of QQ bacteria solution or QQ carriers inevitably leads to unpredictable effects on MBR microbial systems and operational efficiency (for example, reduced stability of nitrification and denitrification processes, reduced biodegradation efficiency and unbalanced biofilm formation etc.). Here, we present a biohybrid membrane called ES-BM (electrospinning-biohybrid membrane), which features a unique pore size structure consisting of electrospun superhydrophilic nanofiber sheaths, a self-QQ layer (active QQ bacteria are immobilized within the interlayer structure of this biohybrid membrane to inhibit the QS process of biofilm-forming associated bacteria at the source surface where membrane biofouling occurs), and a basement filter layer, which maintain the activity of QQ bacteria for an extended period. The ES-BM extends operational cycles up to 21 days at a constant flux of 24 L/m²/h, which is three times longer than conventional MBR systems. The membrane exhibits exceptional hydrophilicity (water contact angle of approximately 0° within 2 seconds) and high tensile strength (Young’s modulus of 135 MPa). Long-term bioactivity tests confirm the stability and recyclability of the ES-BM. Additionally, microbial community analysis suggests that the biohybrid membrane suppresses the growth of biofilm-related bacteria without significantly affecting the indigenous microbial population, further enhancing system performance. This work demonstrates the potential of ES-BM for improving MBR biofouling resistance and presents insights into scalable electrospinning fabrication techniques.

Modeling of the interaction of stressful components agricultural production

There is a completely natural, organic nonlinear relationship between crop production and animal husbandry, which are crucial components of agricultural production in Ukraine. Timely and appropriate management of these subsystems contributes to the stable growth of the country’s agriculture with minimal risk. This approach requires improvements in terms of the digitalization of the economy, particularly in the context of applying computer modeling to the nonlinear processes of interaction between these components. The article develops a modern methodology for computer modeling of an economic management object—a thorough study of a nonlinear dynamic model of the VolterraLotka class, featuring a component that characterizes the increase in livestock profitability due to feed supply. The model takes into account various influencing factors, allowing for the assessment of the efficiency of the interaction between crop production and animal husbandry at different stages of agricultural production. The study examines the behavior of the dynamic model in the vicinity of the leverage point, analyzing the modeled trend dependencies and statistical components: in the vicinity of the equilibrium point, there are oscillatory movements with a certain defined period, and the solutions of the mathematical model, i.e., integral curves, over time reflect the seasonal nature of the interaction between crop production and animal husbandry. The behavior of virtual scenarios—integral curves and phase portraits based on the mathematical model of nonlinear interaction of agricultural production components—wasstudied, showing the location of the equilibrium point, extreme points, and other critical points for the respective curves in a specific coordinate system. A transition to a dimensionless dynamic model and an economic interpretation of its implicit solution were indicated. Additionally, the impact of external economic factors on the stability of the system was analyzed, allowing for better forecasting of potential risks and the preparation of appropriate strategies to minimize them. For the first time, an approximate numerical estimate of the economic risk measure of the evolution of the interaction and interplay of agricultural subsystems over time was carried out in the study of the nonlinear dynamic model of the economic management object. The obtained results can be used to improve management strategies in the agricultural sector, particularly to enhance the stability of production processes and reduce economic risks in the context of market instability and climate change. This research provides new opportunities for effective planning and the implementation of innovations in Ukraine’s agricultural sector.

Stability of Weyl Node Merging Processes under Symmetry Constraints.

Changes in the number of Weyl nodes in Weyl semimetals occur through merging processes, usually involving a pair of oppositely charged nodes. More complicated processes involving multiple Weyl nodes are also possible, but they typically require fine tuning and are thus less stable. In this Letter, we study how symmetries affect the allowed merging processes and their stability, focusing on the combination of a twofold rotation and time-reversal (C_{2}T) symmetry. We find that, counterintuitively, processes involving a merging of three nodes are more generic than processes involving only two nodes. Our Letter suggests that multi-Weyl merging may be observed in a large variety of quantum materials, and we discuss SrSi_{2} and bilayer graphene as potential candidates.

Oxygen‐Stable Electrochemical CO2 Capture using Redox‐Active Heterocyclic Benzodithiophene Quinone

AbstractElectrochemical carbon capture offers a promising alternative to thermal amine technology, which serves as the traditional benchmark method for CO2 capture. Despite its technological maturity, the widespread deployment of thermal amine technologies is hindered by high energy consumption and sorbent degradation. In contrast, electrochemical methods, with their inherently isothermal operation, address these challenges, offering enhanced energy efficiency and robustness. Among emerging strategies, electrochemical carbon capture systems using redox‐active materials such as quinones stand out for their potential to capture CO2. However, their practical application is currently limited by their low stability in the presence of oxygen. We demonstrate that benzodithiophene quinone (BDT‐Q), a heterocyclic quinone, exhibits high stability in electrochemical carbon capture processes with oxygen‐containing feed gas. Conducted in a cyclic flow system with a simulated flue gas mixture containing 13 % CO2 and 3.5 % O2 for over 100 hours, the process demonstrates high oxygen stability with an electron utilization of 0.83 without significant degradation, indicating a promising approach for real world applications. Our study explores the potential of new heterocyclic quinone compounds in the context of carbon capture technologies.

Oxygen-Stable Electrochemical CO2 Capture using Redox-Active Heterocyclic Benzodithiophene Quinone.

Electrochemical carbon capture offers a promising alternative to thermal amine technology, which serves as the traditional benchmark method for CO2 capture. Despite its technological maturity, the widespread deployment of thermal amine technologies is hindered by high energy consumption and sorbent degradation. In contrast, electrochemical methods, with their inherently isothermal operation, address these challenges, offering enhanced energy efficiency and robustness. Among emerging strategies, electrochemical carbon capture systems using redox-active materials such as quinones stand out for their potential to capture CO2. However, their practical application is currently limited by their low stability in the presence of oxygen. We demonstrate that benzodithiophene quinone (BDT-Q), a heterocyclic quinone, exhibits high stability in electrochemical carbon capture processes with oxygen-containing feed gas. Conducted in a cyclic flow system with a simulated flue gas mixture containing 13 % CO2 and 3.5 % O2 for over 100 hours, the process demonstrates high oxygen stability with an electron utilization of 0.83 without significant degradation, indicating a promising approach for real world applications. Our study explores the potential of new heterocyclic quinone compounds in the context of carbon capture technologies.

Regulators for ensuring the sustainability of reproductive processes in industrial fruit growing

The necessity of developing a system of regulators to ensure the sustainability of reproductive processes in industrial fruit growing is substantiated. An assessment of the efficiency of fruit production in the Russian Federation is given. The factors influencing the decrease in the stability of reproductive processes in industrial fruit growing are identified: an increase in the cost of purchased resources; high cost of finished products; a reduction in the share of subsidies in the created cost of planting; the insufficiency of agricultural producers’ own financial resources for carrying out planned plantings renovations, updating production infrastructure funds and carrying out current production activities. Functional imbalances in the organization of reproductive processes in industrial fruit growing have been identified: internal structural imbalances, high resource intensity of production and technological processes, non-compliance with optimal comparability of production and economic indicators. Generalizing criteria for the sustainability of reproductive processes are systematized: the ability of the system to withstand negative impacts of an economic and natural nature; increasing the possibilities of expanded reproduction of all used resources; ensuring qualitative changes in the production, socio-economic, environmental parameters of the system; increasing the conditions for subsequent improvements, preventing production declines. The article characterizes and evaluates the effectiveness of existing regulators to ensure the sustainability of reproductive processes in industrial fruit growing (macroeconomic, technical, technological and economic). A system of regulators has been developed to ensure the stability of reproductive processes in industrial fruit growing in functional areas of influence. An algorithm is proposed to substantiate the necessary dimensionality of regulators to ensure the stability of reproductive processes in industrial fruit growing.

The Ecology and Evolution of Beavers: Ecosystem Engineers That Ameliorate Climate Change

Beavers, Castor canadensis in North America and Castor fiber in Eurasia, are widely referred to as nature's engineers due to their ability to rapidly transform diverse landscapes into dynamic wetland ecosystems. Few other organisms exhibit the same level of control over local geomorphic, hydrologic, and ecological conditions. Though freshwater ecosystems are particularly vulnerable to changing climate, beavers and their wetland homes have persisted throughout the Northern Hemisphere during numerous prior periods of climatic change. Some research suggests that the need to create stable, climate-buffered habitats at high latitudes during the Miocene directly led to the evolution of dam construction. As we follow an unprecedented trajectory of anthropogenic warming, we have the unique opportunity to describe how beaver ecosystem engineering ameliorates climate change today. Here, we review how beavers create and maintain local hydroclimatic stability and influence larger-scale biophysical ecosystem processes in the context of past, present, and future climate change.

AI-based spatially resolved parameter prediction in laser metal deposition for increased process stability

In the additive manufacturing of components using powder-based laser metal deposition (LMD), the heating of the volume during buildup is a decisive factor for process stability and contour accuracy. If the process parameters remain constant, this intrinsic heating leads to deviations in the deposited layer thickness during the process because of changes in the melt pool volume. This leads to contour deviations and potentially causes the process to fail if the process parameters are no longer within the suitable range. Particularly in the case of complex geometries, this previously required time-consuming process development for adapted process parameters and buildup strategies. This paper examines the potential of data-driven approaches to enhance the stability and precision of LMD processes. To this end, a machine learning (ML) model is employed to optimize laser power settings. The objective of the study is to reduce the thermally induced geometric deviations that often occur during the LMD process by utilizing experimental data. The methodology employs the use of the alloy Inconel 718, renowned for its high strength and temperature resistance, in conjunction with the utilization of computer numerical control machines equipped with laser and imaging systems. The ML model is trained to predict the optimal laser power required to obtain consistent melt pool properties. The results demonstrate that the ML approach is an effective means of reducing geometric deviations.

Superhydrophobic pancake-like graphene oxide for zero liquid discharge solar desalination of real brines

Solar interfacial desalination offers a promising solution to meet the demand for portable water, especially in arid regions. Although various materials have demonstrated high solar-to-steam conversion efficiencies in concentrated solutions, most studies have utilized simulated solutions rather than real seawater. Herein, we developed a pancake-like graphene oxide photothermal membrane with superhydrophobic properties optimized for interfacial heating to desalinate real seawater and brine. Under 1 sun, the membrane efficiently achieves a sustained high evaporation rate of 1.23 kg.m−2.h−1 with a photothermal conversion efficiency of 80 %, while remarkably facilitating salt harvesting. Notably, the membrane maintained stable performance and exhibited no salt accumulation on its surface when tested outdoors with real seawater, demonstrating its practical scalability. The membrane exhibited long-term stability in desalination processes, with full performance restoration through an energy-free cleaning method. These results highlight a potential pathway toward zero-liquid discharge desalination.

City Boundaries—Utilizing Fuzzy Set Theory for the Identification and Localization of the Urban–Rural Transition Zone

This article examines the potential of fuzzy set theory for analysing gradual changes in land use patterns within peri-urban areas. The primary objective of the study was to propose a methodology based on fuzzy set theory for the precise delineation of city boundaries and the identification and spatial localisation of the urban–rural transition zone. The analysis focused on elucidating the defining parameters of this area and the scope of land use changes within the urban–rural transition zone. The analysis employed data from four discrete time points. The data were collected in 2005, 2010, 2017, and 2022. The characteristics of the urban–rural transition zone were evaluated through an examination of historical data and the current land use patterns in regions experiencing direct urbanization pressure. The study demonstrated that, although spatial barriers remain, the city’s development has continued at a consistent pace. Between 2005 and 2010, the area of land classified as urban exhibited a 10% increase, with a further 7% increase observed in the subsequent period, spanning 2010 to 2017. In the most recent period under examination, the urban land area increased by 9%, a figure that is consistent with the rates observed in previous years. These results indicate the stability of urbanization processes in the analysed city, while also revealing significant changes in the limits of urban development and in the intensity of land use. The research project concentrated on the city of Olsztyn and the neighbouring suburban areas, which are subject to direct influence from the city’s expansion. The area under study encompasses 202.4 km2 within an eight-km radius of the city centre. The authors of the study emphasized the necessity for systematic monitoring of changes in the transition zone between urban and rural areas. This is to ensure effective control of spatial development and ongoing adjustment of planning tools to effectively prevent uncontrolled expansion. The methodology used enabled the precise delimitation of urban development and the transition zone. This allowed for an in-depth analysis of changes in land use intensity.

Polyoxometalate‐Derived Photocatalysts Enabling Progress in Hydrogen Evolution Reactions

AbstractPhotocatalytic water splitting is capable of converting abundant solar energy into environmentally friendly and renewable chemical energy, presenting a promising solution to alleviate the energy crisis and combat environmental pollution. The development of high‐performance photocatalysts is crucial for significantly improving the efficiency of the hydrogen evolution reaction (HER) involved. Polyoxometalate (POM)‐derived materials, known for their tunable compositions, diverse structures, electron storage/release capabilities, as well as quasi‐semiconductor photochemical properties, serve as highly efficient catalysts in sustainable photosynthesis. This comprehensive review navigates the latest advancements in the assembly strategies and HER performance of POM‐based crystalline materials. It also discusses the composite materials formed by infiltrating POM into metal‐organic frameworks (MOF) and examines the roles of transition metal compounds derived from polyoxometalates, such as sulfides and carbides, in photocatalytic HER. Emphasis is placed on the prospects for the future development of POM‐based compounds as photocatalysts, along with several strategies and outlooks that could facilitate their progress. POM‐derived materials are believed to have significant potential to enhance hydrogen production efficiency while maintaining thermal stability in HER processes.

Comprehensive assessment of factors affecting the operational reliability of low-voltage asynchronous electric motors of a coal mining complex

THE RELEVANCE of this study lies in solving the problem of reliable functioning of elements of energy systems and ensuring their effective operation during open-pit mining. The paper presents a methodological approach that allows us to assess the level of reliability of low-voltage asynchronous electric motors in a coal mine with complex mining, geological and climatic conditions of production. THE PURPOSE of the work is to quantify the operational factors affecting the service life of an asynchronous electric motor with a short-circuited rotor. Attention is focused on how influencing factors, different in physical basis, among which electrical parameters are highlighted – the coefficient of voltage asymmetry in the reverse sequence, the coefficients of harmonic voltage components and environmental parameters – temperature, air humidity and dustiness, affect the dynamics of changes in the service life of an asynchronous electric motor. Asynchronous electric motors used at one of the enterprises of JSC SUEK in the Trans-Baikal Territory are considered as an object of research. METHODS. The main tool for the implementation of research tasks is computer modeling based on the Matlab software package. RESULTS. The studies were performed on an asynchronous electric motor with a short-circuited rotor with Ph = 3 kW, rated speed 1500 rpm. The simulation of the operating mode of the electric motor under study was performed by changing the experimental parameters: the values of the total coefficient of harmonic voltage components (KU) – from 4 to 12% with a range of 2%; the values of the voltage asymmetry coefficient in the reverse sequence (K2U) – from 0 to 4% with a range of 1%; the ambient temperature (∆Tокr) – from -30°C to +30°C with a range of 10°C; air humidity values (Vc) – 20% and 60%; dust thermal conductivity coefficient values (Kт) – 0,12 and 0,28. Based on the obtained research results, diagrams are constructed that clearly illustrate the dynamics of changes in the service life of an asynchronous electric motor depending on the combination of influencing factors. CONCLUSION. The trends in solving the issues of reliable functioning of a coal mining enterprise with the presence of asynchronous electric motors and ensuring their efficient operation are the most priority, mainly focused on maintaining the stability of technological processes and maintaining the production volumes of a coal mining enterprise. The stability of the electric motor to certain influencing factors is estimated and their critical values are established. Recommendations on the use of asynchronous electric motors are formulated, taking into account their operating conditions.