ВЫБОР ОБЪЕКТОВ ДЛЯ КОНТРОЛЯ ТЕХНИЧЕСКОГО СОСТОЯНИЯ САМОХОДНЫХ СЕЛЬСКОХОЗЯЙСТВЕННЫХ МАШИН

Typically, the reliability indicators of radio-electronic equipment (probability of failure-free operation, mean time to failure, failure rate, and availability factor) are assessed through tests or statistical analysis. However, in modern conditions, when dual-purpose technical systems of foreign manufacture with limited input information are used in the armed forces, it is not possible to qualitatively assess the degree of reliability of these samples. To solve this problem, it is proposed to rely on the engineering characteristics of armament samples, such as vibration resistance, structural and parametric redundancy, and durability. The article examines the calculation of classical reliability indicators for radio-electronic equipment and proposes methods for comparing these indicators with the engineering characteristics of the controlled object. Practical recommendations are provided for maintenance personnel on assessing the reliability of radio-electronic equipment based on the engineering characteristics of the controlled object. The use of the proposed approach allows for the assessment of radio-electronic equipment reliability using an appropriate methodology during visual inspection and analysis of the product's block diagram, determining the degree of vibration resistance, parametric redundancy, and durability. As a result, the subjectivity of assessments is reduced. The relevance of the work is due to the widespread use of foreign-made dual-purpose technical systems in the armed forces. In most cases, the manufacturer of such systems does not permit the repair of the provided equipment in another country. Therefore, the equipment user (maintenance personnel, engineering and technical staff) is forced to find ways to integrate the received equipment into the existing maintenance and repair system, and methods for assessing the reliability of such equipment. The methodologies are suitable for samples of foreign-origin radio-electronic equipment supplied without technical documentation and information on manufacturing, storage, and testing conditions. The results can be applied in the security and defense sector of Ukraine for the integration of received armaments into the current repair and maintenance system.

Machinery condition monitoring has entered the era of big data and some research has been done based on big data. Abnormal segments, such as missing segments and drift segments, are inevitable in big data acquired from harsh industrial environment due to temporary sensor failures, network segment transmission delays, or accidental loss of some collected data and so on. Being independent of the machinery condition, the abnormal segments not only reduce the quality of the data for condition monitoring and big data analysis, but also bring a heavy computation load. However, there are few reports to address abnormal segment detection for further data cleaning in the field of machinery condition monitoring. Therefore, an abnormal segment detection method is proposed to improve the quality of big data. First, a sliding window is used to separate the data into different segments. Then, 14 kinds of time-domain features are extracted from each segment and principle component analysis (PCA) is employed to extract the principle components from these features. In addition, local outlier factor (LOF) is calculated based on the principle components to evaluate the degree of being an outlier for each segment. Finally, the data, including a drift segment from a real wind turbine, are used to verify the effectiveness of the proposed method.

The use of modern digital technologies during the industrial revolution enables to revise a number of approaches to the organization of technological processes, in particular when introducing approaches to the implementation of repair programs of energy enterprises. Through the example of the network planning and control system, the use of the overhaul activity schedule for generating equipment is considered, taking into account the logging of asbuilt documentation in a digital system, which is a software and technical complex made up of a centralized data storage system and a decentralized registry. The improvement of equipment, the development of diagnostic tools and methods directly affects the maintenance and repair system. In the maintenance system under development, it is planned to make a transition from statistical empirical assessments of the technical condition of equipment to objective ones based on automated technical diagnostics systems. On the basis of an algorithm for implementing a technical condition-based equipment repair program for energy enterprises, the authors proposed an algorithm for conducting technical supervision and recording the stages of work performed in a distributed register, based on the capabilities of modern digital data collection and processing systems. Obtaining parameter values for further use in the operation of the proposed algorithm is carried out on the basis of the capabilities existing at energy facilities of information-measuring and control systems. The use of the network planning and management system in the form of a network schedule and the algorithm proposed by the authors for conducting technical supervision and recording the stages of work performed during repair activities will make it possible to objectively determine the amount of labor resources necessary to perform the planned scope of work within the specified period, identify critical works delaying the completion of repair, actively manage repair by analyzing the progress of repair work and making reasonable organizational and technical decisions that ensure the performance of work within the planned time frame and at the lowest possible costs.

The article suggests a technique for parameters determining of a maintenance and repair system (MRS) for a geographically dispersed park of technical systems (PTS). The solutions of problems of this class assume the formation, as a rule, of the topological and functional structures of the system. In addition, for geographically dispersed fleet of vehicles, it is necessary to solve the problem of distributing equipment that requires maintenance to service areas. The solution of the problem in such a formulation requires the consideration of a large number of heterogeneous factors (variables in the formalized representation of the problem). And this leads to a large dimension of the problem, which makes it difficult to obtain acceptable solutions by known methods. To overcome these difficulties, the article proposes a technique for solving such problems based on its decomposition into three problems (tasks of three levels) - the task of forming requests for maintenance, the task of forming the topological structure of the system and the task of forming the functional structure of MRS. To solve each of the problems, its formulation and methods of solution are proposed. At the first level, it is advisable to simulate the processes of changing the technical state of the PTS samples and forming applications for its servicing. Applications must be formed in such a way as to optimize the reliability (availability) of technical systems and (or) the costs of their operation. At the second level, taking into account the existing applications, it is necessary to model the functioning of the MRS elements, optimize the PTS readiness indicators and operational costs by selecting the MRS topology and the operational strategies of its elements, and by optimally distributing the maintenance and repair tasks according to the levels and elements of the system. At the third level, it is necessary to calculate and minimize the capital costs for the construction of the MRS and operating costs for various options for its construction, various ways of distributing the maintenance tasks and repairing the PTS by levels and elements of the system to make decisions about the meaning of the maintenance and repair parameters. The proposed methodology makes it possible to obtain acceptable solutions for large-dimensional problems and heterogeneous factors (task solution variables).

The features extracted from multisensory measurements can be used to characterize machinery conditions. However, the nonlinearity and uncertainty presented in machinery degradation process pose challenges on feature selection and fusion in machinery condition monitoring. To alleviate these issues, this paper presents a new probabilistic nonlinear feature selection and fusion method, named probabilistic kernel factor analysis (PKFA). First, the mathematical structure of the PKFA is formulated incorporating kernel techniques on the basis of conventional factor analysis (FA). Next, a PKFA-based machining tool condition monitoring model with support vector regression is presented. The effectiveness of the scheme is experimentally verified on a machining tool testbed. The experimental results show that the proposed PKFA method provides more accurate tool condition prediction than using all initially extracted features and other feature selection techniques (e.g., kernel principal component analysis and conventional FA), and thus confirms its utility as an effective tool for machining tool condition assessment.

The main target of repair and maintenance system (hereinafter referred to as RMS) is target reliability rate maintenance at all stages of rolling equipment technical operation. Development and implementation of improved reliability rate of new wagon generation, safety running indicator maintenance, present fleet of wagons maintenance in the context of long operating life, insufficient providing of repair depot with spare parts and other materials, infrastructure aging requires RMS efficiency upgrading. Current maintenance and freight wagons repair system requires changes that concern not only car-mileage optimization between scheduled repair, but also transition to new strategies of RMS.This article concerns positive and negative aspects of different strategies of maintenance and repair, possibilities of their implementation in RMS of freight wagons. The algorithm of RSM strategy is suggested. It is based on integrated analysis of freight wagon reliability taking into account those construction units that limit the time between maintenance and repair. In addition crucial task is sufficient minimum number of controlled variable for obtaining the information about diagnosing object’s current state. This task requires improvement of separate units technical condition diagnosis programs. Based on obtained data mathematical models for current operation process and RMS impact on freight wagon fault are developed.

Premature aging and cancer in nucleotide excision repair-disorders

The time derivatives of acceleration offer a great advantage in detecting impact-causing faults at an early stage in condition monitoring applications. Defective rolling bearings and gears are common faults that cause impacts. This article is based on extensive real-world measurements, through which large-scale machines have been studied. Numerous laboratory experiments provide additional insight into the matter. A practical solution for detecting faults with as few features as possible is to measure the root mean square (RMS) velocity according to the standards in the frequency range from 10 Hz to 1000 Hz and the peak value of the second time derivative of acceleration, ie snap. Measuring snap produces good results even when the upper cut-off frequency is as low as 2 kHz or slightly higher. This is valuable information when planning the mounting of accelerometers.

-In industrial plants, the profitability of the plant is significantly affected by the quality of machines maintenance. To ensure continuous production, the high valued machines should be kept in good working conditions. This brings plants to search for means to control and reduce equipment failures. When faults emerge in plants, appropriate actions for fault diagnosis and troubleshooting must be executed promptly and effectively to prevent large costs due to breakdowns. To provide reliable and effective maintenance support, the aid of advanced decision support technology utilizing previous repair experience is of crucial importance for the expert operators as it provides them valuable troubleshooting clues for new faults. Artificial intelligence (AI) technology, particularly, knowledge-based approach is promising for this domain. It captures efficiency of problem solving expertise from the domain experts; guides the expert operators in rapid fault detection and troubleshooting. This paper focuses on the design and development of a Knowledge-Intensive Decision Support System (KI-DSS) for Maintenance, Repair and Service in industrial plants to support better maintenance decision and improve maintenance efficiency. With integration of case-based Reasoning and ontology, the Ki- DSS not only carries out data matching retrieval, but also performs semantic associated data access which is important for intelligent knowledge retrieval in decision support system. A case is executed to illustrate the use of the proposed KI-DSS to show the feasibility of our approach and the benefit of the ontology support.

The aim of the study is to analyze, systematize, and formulate scenarios for managing the integration of digital and intelligent technologies in the informatization of education based on the influence of the factors of the existing external environment. It was shown that digital transformation is a process of digital technology integration into all aspects of business activities, requiring fundamental changes in technology, culture, operations, and principles of creating new products and services. Simulation models of digital and intelligent technologies in informatization of education are proposed. Possible scenarios for the development of the education system are described: inertial and transformational. A new viable base scenario is proposed, which can be called a divergent, or school dilution scenario. It is illustrated that these three rather general scenarios show the possible place and role of digital and intellectual technologies in the changes taking place in the informatization of education today.

To improve the system of maintenance and repair, the criterion of rationality of the system of maintenance and repair of engines of mining vehicles is determined, taking into account the costs of maintenance and repair, as well as the type of repair enterprise and the operating time of engine parts. By reducing the cost of maintenance and repair and increasing the engine resource, the efficiency of a rational maintenance and repair system is achieved.

Evaluating the Impact of Spare Parts Pooling Strategy on the Maintenance of Unreliable Repairable Systems

System performance-based joint importance analysis guided maintenance for repairable systems

Small enterprises operate in an environment of increased volatility, where success increasingly depends not on the scale of resources but on the ability to rapidly change key parameters of activity: sales channels, product offerings, process configurations, and interactions with customers and partners. Under these conditions, economic mobility becomes a key prerequisite for the viability and development of small businesses. At the same time, digital technologies (platforms, cloud services, automation and analytics tools, digital communications, and fintech solutions) are shaping a new operational environment that can accelerate management cycles, reduce coordination costs, and expand an enterprise’s range of controllable actions. However, in the SME sector, digitalization remains uneven in both scope and effectiveness: digital solutions are often implemented fragmentarily, without integration with processes and staff competencies, which fails to ensure a sustainable capacity for rapid change. This creates a need for a scientifically grounded explanation of the mechanisms through which digital technologies shape the economic mobility of small enterprises and for identifying the conditions under which digitalization becomes a reproducible managerial capability. For Ukraine, this issue is of heightened importance, as digital tools are not only a factor in competitiveness but also a condition for business resilience and recovery amid high uncertainty, logistics disruptions, energy risks, and increasing cyber threats. The purpose of the study is to substantiate the impact of digital technologies on the formation of economic mobility for small enterprises and to identify the mechanisms through which digitalization reduces the costs and time required for transitions between managerial alternatives, accelerates the management cycle, and expands opportunities for controlled maneuvering. In scientific terms, the economic mobility of a small enterprise reflects a business’s ability to adjust its activity parameters in a controlled manner in response to external shifts while maintaining process continuity and management effectiveness. Its content is revealed through an interrelated system of components: adaptability (the speed of transition from an external signal to a decision), flexibility (restructuring processes without loss of controllability), scalability (changing activity volumes with minimal losses), market agility (reorientation between segments and sales channels), and resource maneuverability (operational redistribution of financial, human, and time resources). To analyze the impact of digitalization on the economic mobility of small businesses, digital technologies are structured by their functional roles in enabling rapid adaptation and in allowing enterprises to reorient between markets. The proposed typology covers six complementary groups: infrastructure solutions; digital sales and marketing technologies; platform ecosystems; operational management systems; analytical and intelligent technologies; and financial-digital tools. Each group strengthens a specific aspect of mobility and creates conditions for synergistic effects when integrated. In the context of economic mobility, digitalization primarily reduces the costs and time required to switch between managerial alternatives. A tangible effect arises not so much from the isolated implementation of digital solutions as from their coordinated use as a “portfolio” of technologies integrated with managerial practices. Under such conditions, enterprises make decisions more quickly and have a broader set of response options to changes in demand, competition, and external constraints, thereby minimizing intuitive decision-making and reducing the cost of managerial errors. Thus, digital technologies are an essential factor in the formation of economic mobility of small enterprises, as they minimize adaptation time and costs and enhance the controllability of change. Their effectiveness is realized when digital channels, operational systems, and analytics operate in a coordinated manner and are supported by process discipline and staff digital competencies. Keywords: economic mobility, small enterprises, digital technologies, digitalization, adaptability, business process flexibility, scalability, management cycle, digital maturity, business resilience.

AI Applications in Health Sector: Use of Artificial Intelligence in Covid-19 Crisis and Impacts of Medical Robots on Global Economy