Journal articles on the topic 'Mining equipment and technology services'

In recent years, with the application of sensors, data acquisition equipment and other modules with sensing ability in the service of complex products, the operation and maintenance system of complex products has become increasingly digital and intelligent. New-generation information technologies such as big data, cloud computing, Internet of Things, mobile Internet, augmented reality (AR) and virtual reality (VR) have also been rapidly applied in the operation and maintenance of complex products. Real-time, multi-source, and massive data has become the basis for decision-making. Data-driven intelligent services have become the development direction of modern manufacturing services. This paper introduces the connotation of intelligent manufacturing and the characteristics of industrial big data, analyzes the application status of data mining technology in intelligent manufacturing, and envisages the future application trend.

Abstract The article deals with the organization of a single technological space for technical diagnostics, maintenance, and repair of mining equipment. The digital technology that unites all services related to production, diagnostics of technical condition, maintenance and repair of mining equipment is based on the SAFE PLANT software package, which provides globality, scalability, versatility, integrability, modularity, distribution, and functionality. The article reflects the results of the implementation of the system at an industrial enterprise.

Investigation of failures is one of the critical activities of mining and haulage equipment operability assurance in mining. Maintaining failure investigation at the required quality level, it is possible to identify provisions, rules and procedures that should be revised or changed, operation conditions that should be improved, additional personnel training, if required, etc. Investigation of failures in mines is under responsibility of machine men and electricians of maintenance and operation services. In reality, factory management and setup for production condition weak concernment of these workers in quality investigation aimed at finding of sources of equipment failures. This article describes real-life results achieved in development and use of maintenance service operation, technology and management monitoring. The requirements are substantiated for quality improvement in failure cause finding and removal in mining and haulage equipment at Chernogorsky open pit mine, SUEK-Khakassia. Causes of the present quality of failure investigation by machine men of Chernogorsky Repair and Engineering Works and Chernogorsky open pit mine are revealed. The proposed recommended practices will improve quality of mining and haulage equipment failure investigation.

With the wide application of artificial intelligence and big data technology in the medical field, the problems of high cost and low efficiency of traditional pharmacy management were becoming more and more obvious. Therefore, this paper proposed to use data mining technology to design and develop the dispensing process and equipment of intelligent pharmacy. Firstly, it summarized the existing data mining technology and association rule methods and expounded its application value in the related fields. Secondly, the data standard and integration platform of dispensing in intelligent pharmacy were established. Web service technology was used to design the interactive interface and call it to the intelligent device of pharmacy. Finally, an intelligent pharmacy management system based on association rule mining was constructed through the data mining of intelligent pharmacy equipment, in order to improve the intelligence and informatization of modern pharmacy management. For the emergency dispensing process of intelligent equipment failure, data mining was used to optimize the intelligent pharmacy equipment and dispensing process and change the pharmacy management from traditional prescription to patient drug treatment, so as to improve the dispensing efficiency of intelligent pharmacy equipment. Through the systematic test and analysis, the results showed that through the real-time risk prevention and control, the formula accuracy and operation speed of the intelligent dispensing machine were improved and the dispensing time was shortened. Through intelligent drug delivery, the unreasonable drug use of patients was reduced, the safety and effectiveness of clinical drug use were ensured, and the contradiction between doctors and patients was reduced. This study can not only optimize the medical experience of patients and provide patients with more high-quality and humanized pharmaceutical technical services but also provide some support for the intelligent management of modern hospitals.

Information technology (IT) infrastructure refers to the combined set of network, software, hardware, applications, and all the information technology-related equipment for an enterprise IT environment. In addition, it provides the entire skeleton for an organization to continue delivering several services to its internal members (employees) and external ones (customers/partners). The interruption of services leads to a significant deterioration of the infrastructure, and at the same time, it slows down their functioning. Additionally, it can result in important loss of user trust. Therefore, we need to proactively help the technician teams to assess the quality and availability of their IT infrastructure. This study may help to build an approach for an IT infrastructure called MAITD-2 in order to classify, analyze, and take problems to closure in a short time face to a multi-criteria decision-making problem.

With the rapid development of computer technology and network technology and the widespread popularity of electronic equipment, communication among people is more dependent on the Internet. The Internet has brought great convenience to people’s lives and work, and the Internet data is constantly being recorded. People’s data information and behavior information, which provides the basis for data mining and recommendation systems, mining users’ information and behaviors, and providing “user portraits” for each user, can provide better services to users and it is also an important part of the recommendation system. In one step, this article takes MOOC education resources as the research goal. In order to improve the effective management of MOOC platform resources based on traditional methods, this article combines relevant data sets and recommendation techniques to initially build a learning platform, implements a deep neural network algorithm, and recommends related services. The request and response data were explained, and through the online learning data set, based on the learner’s historical learning records, the learning resources were simulated and recommended to the learners. The resource customization module was elaborated. Through the results of resource recommendation, a personalized learning resource recommendation platform was initially realized, which more intuitively demonstrated the recommendation effect and better realized the teaching management of the MOOC platform.

This research proposes a novel strategy for constructing a knowledge-based recommender system (RS) based on both structured data and unstructured text data. We present its application to improve the services of heavy equipment repair companies to better adjust to their customers’ needs. The ultimate outcome of this work is a visualized web-based interactive recommendation dashboard that shows options that are predicted to improve the customer loyalty metric, known as Net Promoter Score (NPS). We also present a number of techniques aiming to improve the performance of action rule mining by allowing to have convenient periodic updates of the system’s knowledge base. We describe the preprocessing-based and distributed-processing-based method and present the results of testing them for performance within the RS framework. The proposed modifications for the actionable knowledge miner were implemented and compared with the original method in terms of the mining results/times and generated recommendations. Preprocessing-based methods decreased mining by 10–20×, while distributed mining implementation decreased mining timesby 300–400×, with negligible knowledge loss. The article concludes with the future directions for the scalability of the NPS recommender system and remaining challenges in its big data processing.

Complicated product lifecycle information including design and manufacturing, operation and maintenance as well as relative supply information, all are tightly related to the product life cycle cooperative design and the process of establishing the dynamic alliance. Data grid includes the digital library and data grid service technologies and it can provide the reliable technique support to integrated information systems. The grey clustering is used to merge the same type of factors based on presetting conditions. The improved grey clustering algorithm has been used to find the main failure types for some equipment. The structure of the multi layers and cross information share in the dynamic alliance for the ship life cycle information based on two data grid service centers and the flows of resources and information discovery based on data mining are proposed according to the information share requirements. A developed protocol system based on two data grid services has been presented to show ship lifecycle information share and finding the main failure types of pumps using grey clustering algorithm.

The purpose of this paper is to study the characteristics of the production process in the Quebec economy. We devote particular attention to two features of the technology: the returns to scale and the substitution possibilities. Two forms of production functions, the Cobb-Douglas and an homothetic translog production function, are estimated for six branches of economic activity. These are: Agriculture; Fishing and Forestry; Mining; Quarying and Oil Wells; Manufacturing; Utilities; Services. Two main conclusions are derived from this work. First, there is strong evidence of constant returns to scale in all branches of the Quebec economy but services. Second, when comparing the Cobb-Douglas model with an homothetic translog model, the hypothesis that the true model is the Cobb-Douglas one cannot be rejected for five of our six sectors. Therefore, there is evidence that the elasticity of substitution is around one. Finally a byproduct of our work has been the construction of capital stock series for the Quebec economy (1960-73) disaggregated into 14 sectors, and two types of capital: construction and machinery and equipment.

Introduction. The article considers the organization of heading and winning machines’ maintenance in the mines of the Upper Kama potash salt deposit highlighting the potential of maintenance and repair according to the actual health of mining machines. Research methodology. The methodological foundations are presented of collecting and processing the data on Ural heading and winning machines failure statistics in the Upper Kama potash salt deposit. It is indicated that monitoring systems implemented in mining machine since 2013 made it possible to quickly track and record data on operating modes and downtime causes. Results. Research revealed that the greatest number of Ural heading and winning machines emergency failures is due to mining technology violation, as well as untimely or poor quality repairs. Breakdowns of swing and distributing reduction gears of planetary actuators, reduction gears of berm bodies and hydraulic systems units are most common. Ural mining machines’ repair cycle is presented. Even complex current and overhauls of heading and winning machines are often carried out by miners who directly operate the machines. Summary. Statistical data storage on failures and corresponding diagnostic parameters limit of heading and winning machines makes it possible to predict the time of equipment failure with a high degree of probability. The more standardized the potash mining machine operation and repair conditions are, the more accurate the remaining life forecast of the residual resource is.

With the development of increasingly advanced information technology and electronic technology, especially with regard to physical information systems, cloud computing systems, and social services, big data will be widely visible, creating benefits for people and at the same time facing huge challenges. In addition, with the advent of the era of big data, the scale of data sets is getting larger and larger. Traditional data analysis methods can no longer solve the problem of large-scale data sets, and the hidden information behind big data is digging out, especially in the field of e-commerce. We have become a key factor in competition among enterprises. We use a support vector machine method based on parallel computing to analyze the data. First, the training samples are divided into several working subsets through the SOM self-organizing neural network classification method. Compared with the ever-increasing progress of information technology and electronic equipment, especially the related physical information system finally merges the training results of each working set, so as to quickly deal with the problem of massive data prediction and analysis. This paper proposes that big data has the flexibility of expansion and quality assessment system, so it is meaningful to replace the double-sidedness of quality assessment with big data. Finally, considering the excellent performance of parallel support vector machines in data mining and analysis, we apply this method to the big data analysis of e-commerce. The research results show that parallel support vector machines can solve the problem of processing large-scale data sets. The emergence of data dirty problems has increased the effective rate by at least 70%.

Relevance. In the current context, the cost of coal products is growing. Labor productivity in coal mines and open-pit mines is significantly lower than the corresponding indicator in North America and Australia, a significant proportion of unprofitable enterprises, despite the fact that a third of the world’s coal resources and a fifth of the proven reserves are concentrated in the Russian Federation. In these circumstances, the substantiation of the strategic development of the coal industry on the basis of a SWOT analysis is of great importance. Purpose of the study is to substantiate the strategic vision for the development of the coal industry, priorities for the functioning of coal mining enterprises. Research methods are scientific generalization, method of system analysis and analogies. Results. In the course of the study, the possibilities of functioning of coal mining enterprises, threats to the coal industry, strengths and weaknesses of their activities were identified. The ability to function is determined by the presence of huge coal reserves in Russia, the leadership in its production and export, and a significant share of coking coal grades. The identified threats include: a significant decrease in prices on the world market and coal consumption in the domestic market, an increase in the average transportation distance and the risks of introducing environmental restrictions. The weaknesses in the activities of coal mining enterprises, requiring appropriate measures to be taken to liquidate them, come down to the following: increased operating costs, low labor productivity, a significant number of small mines and open-pit mines that hinder the effective development of the industry as a whole. At the same time, the strategy for further development should focus on the strengths of the coal mining enterprises. These include lower capital investments based on conventional fuel, significantly lower than in the oil and gas industry, therefore, during the period of ensuring sustainable development of the economy as a whole, the development of the coal industry will require lower costs, which creates conditions for the development of other related industries, the possibility of introducing an economic mechanism of inter-fuel competition, as well as the effective functioning of the market structure within the “free” oligopoly. Increasing the competitiveness of coal mining enterprises requires the use of accelerated depreciation methods at export-oriented enterprises, the introduction of problem-solving technology at large coal mining enterprises, the establishment of a rational ratio of the used imported and Russian equipment, and the containment of the growth in the cost of railway transport services. The focus on the implementation of the concept of creating a digital industrial enterprise in the industry plays a special role. A number of measures should be taken to improve financial stability. Conclusions. The identified opportunities and threats, as well as the strengths and weaknesses of the activities of coal mining enterprises, serve as the basis for substantiating the “Strategy for the development of the coal industry”, determine promising directions for the future of coal mining enterprises.

The development of the economy is related not only to its benefits, but also its negative aspects. One of the negative impacts is the impact on the environment and society. Many types of industry and, in a narrower sense, of enterprises, adversely affect their surroundings. It is one of the many factors that has contributed to the growing popularity of the concept of corporate social responsibility (CSR). It is important to balance business and industry with the environment and community impacts. This study presents selected aspects of corporate social responsibility, such as society, the environment, and corporate governance in relation to the industry responsible for energy production and distribution. This group includes the energy sector (mining oil, gas, consumer fuels, and energy equipment and services), the materials sector (metallurgy and mining), as well as distribution (gas, electricity supply, independent energy producers, and renewable energy). The aim of the article was to present the level of implementation of the concept of corporate social responsibility in enterprises responsible for the production and supply of energy. The article uses the analysis of the literature and the statistical analysis showing the level of use of the described concept in the analysed entities. It was based on an analysis of 1904 companies from 41 countries around the world. The article presents the level of implementation of the concept of corporate social responsibility in selected sectors, divided into three areas: social, environmental, and corporate governance. In each of them, the analysis was performed with regard to the selected, most important factors. In addition, an analysis of the described industry, in relation to the others, is presented, which shows the level of use of individual CSR aspects. Thus, it shows which criteria are followed by enterprises in their activities and indicates the real areas of CSR impact on companies.

Oil and gas companies are starting to invest more in the energy transition and establish emissions-reduction goals, such as an end to routine gas venting and flaring, with some going as far as setting net-zero goals by mid-century. A wide range of climate technologies with varying degrees of maturity levels are needed to pave the road to net zero. These include electrification and grid decarbonization, advances in battery technology, blue and green hydrogen fuels, bioenergy, carbon capture use and storage, and mitigating emissions of potent greenhouse gases such as methane. The COVID-19 pandemic has helped accelerate the pace of the digital transformation in the oil and gas industry. Digitalization is, in effect, a part of the broader energy transition that is occurring in the industry. This includes a move from on-premises data centers to the cloud, building digital twins of physical assets, process automation using the Internet of Things (IoT), leveraging reams of data from oil and gas operations for artificial intelligence/machine leaning (AI/ML) applications, cloud-based high-performance computing for applications such as seismic imaging for carbon capture and storage, and predictive maintenance to fix leaky equipment to reduce the environmental footprint of operations. These technologies serve to improve productivity, increase operational efficiency, reduce downtime, increase cost savings, and reduce the carbon intensity of operations. The International Energy Agency report “The Oil and Gas Industry in Energy Transitions” states that reducing methane leaks to the atmosphere is the single most important and cost-effective way for the industry to bring down these emissions. This is a domain that can benefit significantly from the use of AI/ML techniques for leak detection and remediation (LDAR) efforts. ML techniques such as computer vision and anomaly detection can be used to identify both large and localized methane leaks from remote-sensing data and data streaming in from IoT sensors in the field. A combination of data modalities, with varying spatiotemporal resolutions, together with appropriate AI/ML technologies, would be essential for an effective methane LDAR program. As companies look to reduce their Scope 1, 2, and 3 emissions, breaking down data silos and establishing data standardization with common data models becomes critical in systems integration to develop an optimal emissions-reduction strategy. A seamless flow of information will enable the generation of high-fidelity data sets, which can be used to lower the operational footprint and drive business effects with AI solutions. With cloud-enabled technologies, driven by the application of ML and deep learning, companies can combine speed of implementation with scalability to accelerate their energy-transition efforts. I would like to invite readers to review the selection of papers to get an idea of various applications in the upstream oil and gas space where ML methods have been used. The highlighted papers cover the use of transformer-based models to predict oil production, the use of data analytics to study parent/child well relationships in shale plays, and the use of convolutional neural networks in core analysis. Recommended additional reading at OnePetro: www.onepetro.org. SPE 207744 Accelerating Subsurface Data Processing and Interpretation With Cloud-Based Full Waveform Inversion Systems by Sirivan Chaleunxay, Amazon Web Services, et al. SPE 205443 Natural-Language Processing and Text-Mining Approaches in Production-Shortfalls Analytics: Methodology, Case Study, and Value in the North Sea by Edgar Bernier, Total Denmark, et al. URTEC 208367 Real-Time Applications for Geological Operations: Repeatable AI Use Cases by Alfio Malossi, Eni, et al.

A blowout in Ohio in 2018 was the first ever where the emissions could be measured from space, though it was at best a rough estimate based on data gathered on the 13th day after the XTO Energy well control event began. A year later, a blowout of a Devon well near Victoria, Texas, was measured starting the day after it occurred, with data collected on 3 days over the next 2 weeks. Using the measurement of carbon dioxide, it was estimated that the flare was 87% effective in burning about 4,800 metric tons of the leaking methane gas. Emission estimates varied wildly, and both the Ohio (Pandey et al. 2019) and Texas (Cusworth, Duren, Thorpe et al. 2020) efforts to use satellites led to technical papers to consider how they addressed this challenge. For those with blowouts next year, chances are a lot better methane-emission data would be available because of the launch of a constellation of specialized methane-measurement satellites by the two groups that played a key role in the earlier tests. In presentations at CERAWeek by IHS Markit, GHGSat said it has two methane-detection satellites in orbit and plans the launch of eight more, and the Environmental Defense Fund (EDF) said it is moving forward with the launch of its first one next year. Both are aiming to cover the lion’s share of oil and gas operations and measure the flow rate of the gas rather than concentrations in the atmosphere. They said they can do that far more accurately than was possible with the general-purpose climate observation satellites by focusing their equipment on the wavelength of methane. GHGSat said its satellites, which are about the size of a microwave oven, can measure the potent greenhouse gas from an elevation of 500 km and up. They are placed in polar orbit, which allows them to cover the globe every 2 weeks as the Earth rotates. Launching more satellites will allow more frequent looks. There are differences in the GHGSat and EDF designs, reflecting their contrasting missions. The Canadian company GHGSat, whose satellite initiative was initially supported by Schlumberger and the Oil and Gas Climate Initiative, is building tiny satellites with extremely high resolution to serve clients in the oil and mining businesses. During the presentation, Stéphane Germain, chief executive officer of GHGSat, displayed an image and said its satellites can tell if the methane is “coming from a particular facility and even tell what part of the facility it is coming from.” The company also sells the services of similarly equipped planes that can create more-detailed images using similar equipment at elevations of 3000 m and higher. EDF raised $100 million from donors, including Elon Musk, and has hired Raytheon to build a satellite equipped with a detector from Ball Aerospace. It can survey an area that is 260 km wide. That is far wider than the GHGSat satellites, which have the advantage of being able to zero in on smaller details when looking for leaks. The environmental group points out its device is more sensitive to methane emissions, detecting levels down to two parts per billion.

Changing of country’s leadership will affect state policy in Indonesia. It will automatically change its policies and business processess gradually to make it more clean, well controlled, and more transparant. In this case, it might affect some companies that previously their business rely on the power of negotiation business practice and relationships for achieving a project. That companies will start losing their customers especially from the government and state-owned bank (SOEs) in the future. PT. DXY is a medium scale company engaged in mining industry, particularly in supplying various type of heavy equipments and other support services. The shareholders and the board of directors aware of this situation and they are ready to find a way to transform. Through various stages of approach, especially in usage of the IS / IT from Primozic, SWOT Analysis, Balanced Scorecard, and New Information Economics, they drafted business plans, and information systems and technology (IS/IT) strategies so that the company can still exist and even be able to occupy higher position in the competition of the industry. One that can be addressed here is the new Balanced Scorecard that is used as the benchmark performance management at the company for the first time. Changes in business processes as well as investments in the near future on the IS/IT cover human resource (HR) and customer resource management (CRM) applications along with forming computer networking. It is believed to be able to change the position of the use of IS/IT from what is now saving money becoming making money. Index Terms: balance scorecard, information system and technology, make money, save money, state policy.

In order to realize the automation and intelligence of agricultural equipment mechanical state detection and improve the efficiency and accuracy of agricultural machinery equipment detection technology, this paper proposes an intelligent agricultural machinery equipment state detection method based on computer data mining. This method uses support vector machine to classify the equipment status and uses ant colony algorithm to solve the optimization problem. Its basic logic is to collect the status data of agricultural machinery equipment, extract the status detection characteristics of agricultural machinery equipment, and use computer data mining to establish an automatic state detection model of agricultural machinery equipment. The application results show that the correct rate of the state detection of agricultural machinery equipment is more than 95%, and the false detection rate of the state of agricultural machinery equipment is far lower than that of other current state detection methods of agricultural machinery equipment. Conclusion. This method can realize high-precision real-time detection of agricultural machinery equipment and has higher practical value.

Abstract Mining machinery and equipment have changed little in recent decades, from the point of view of the principle of operation, construction and structure. But in terms of dimensions, performance and stresses they have made a lot of progress, experiencing unprecedented sophistication and complexity. In order to fulfil the new requirements imposed by the increasing productivity and efficiency demands, as well as the economic, environmental and safety constraints, their design and development must comply with the general advance of overall technology. Therefore, recently, modern analytical methods have also been included in the design and development of mining machines. Among other issues, the present paper examines the theoretical and conceptual aspects related to the mining machinery’ design requirements involving mechatronics.

With the resources exhaustion of medium-thick and thick coal seam, the mining technology of thin coal seam has attracted more attention. Due to the little working space for mining in thin coal seam, blasting mining and high-grade conventional mining are main mining methods that were used in thin coal seam. Taking the 17th coal seam of Liyan mine as an example, in this paper we analyze the roof structure of the lower thin coal seam under the goaf of the upper coal seam. The fully mechanized mining equipment is selected on the basis of the new roof structure and applied in field. Finally, safe and efficient mining is achieved by improving the adaptability of the equipment.

The open-up data mining system is one of developing directions of the present data mining system. In this paper we have put forward a data mining system based on the Web Services and given an applied example on the basis of analysis of the system. As the Web Services have stronger sealing and their joints are simple, they make the integration of the data mining system more flexible, heightening the working of the mining system.

Because of mine production, the open-pit enission of coal gangue solid waste and surface subsidence are one of important causes to failure the mining area land and environment, so the key technology, processes and equipment of filling mining to replace coal have been developed, which convergences the existing system of mining technology, And the stability theory of the control of filling mining rock movement and the method of surface subsidence prediction have been established, which provides a scientific basis for equipment Selection and the design of subsidence control; the key technologies of filling mining to replace coal is successfully applicated, which significantly improves the recovery rate of coal resources in China and constructs the new coordinated development model that is combined by the underground disposal of coal waste, mining subsidence control and the “under three”safe coal mining, through the above, the target of green mining and the coordinated development of mining social, economic and environmental will be achieved.

The paper shows the state of the art of identification, formation and development of the clusters in Colombia, collecting topics from the decentralization process in Colombia, the fiscal decentralization and the economic growth; a period of economic changes in the country begins from these two topics, the productive apparatus is prepared to compete with the most demanding markets of Europe, Asia and North America. For carrying out this, it was necessary to change the culture of production, it is not a matter of doing what the entrepreneur wants but to propose new goods and services to the global market, generating a brand value and differentiating them from international competitors; Colombia in the twentieth century opened its doors to foreign trade, and started working on the proposal of economic opening, it was necessary to work on the new Political Constitution of Colombia, from that time there is a change, a work of the National Planning Department, in conjunction with the National Council for Competitiveness, the work is based on proposing new productive bets, this as a strategy to face the competition that was seen coming to the country, with the risk of losing national entries in the market by national companies and on the contrary the international companies would arrive at the national market with new products, innovated and of low price, the national industry would not be able to produce and compete at the prices of the imported goods. One of the initiatives is to form associativity, by means of which productive processes could be improved, more advanced technology would be handled, joint research would be carried out, and work would be done to transfer knowledge, strengthen the productive chain and within the organizations would improve the value chain as a strategic tool, through which the company’s activities and sources of competitive advantage are analyzed; from this, the clusters are being worked on another proposal, which began to revolutionize Colombia’s economic change by moving from an economy based on extractive and mining activity to offering differentiated products with added value, quality was considered an integral part of the good and with a specialized human resource, in this way the regions have made a great social leap, since from this new chain the regions begin to strengthen their economy, to improve their human talent, to manage the supply chain, and above all to export non-mining energy products that in short only leave shortages of products from the family basket, depletes and impoverishes the productivity of their soils, contributing a negative GDP, because in the long time, the land where the mineral exploitation as oil and coal become sterile for that, although at one point they can represent an important sector for the economic activity of the country and reflects in its GDP an important percentage to the economy, this type of economic activity destroys the country’s competitiveness in the long term, so in the medium term can be seen as a lever for economic and social development. The clusters represent a new production alternative for the country as a strategy for local growth, for the Colombian economy in global scenarios means diversification in the exportable supply; for this, it is necessary to define strategies that enable productive transformation in the country, this will provide tools and sophisticated knowledge allowing the productive sector to obtain greater profitability and sustainability over time, to offer products, bines and high quality services [28]. The aim that the cluster network has been working for is the generation and exchange of knowledge among the different actors that are part of the productive alliance formation and cluster dynamization. This objective is evidenced by the success it has had in the Valle del Cauca with the cluster of sugarcane, medical excellence, macrosnacks, care and beauty, white protein, among others.It is for all the above that this work wants to show the importance of the diversification of goods and services of an economy from the synergetic and pooled work that the clusters provide, it is well known that the economies that diversify are those that can compete in the global market since its economic component is not only based on sometimes non-renewable natural resources such as hydrocarbons, but they work with the most important resource that an economy has its human talent, this resource is renewable and it is not exhausted, on the contrary it is transformed, updated, qualified, transferred and it is a know-how for international trade, this term can be understood as preexisting knowledge not always academic, which includes techniques, secret information that is known and handled efficiently and with experience, which has become a valuable intangible asset, this includes the most appropriate way to mix components, equipment used, this personnel that knows how to perform the tasks; all this is mixed in a cluster.

This paper mainly discusses the application of the mass real-time data mining technology in equipment safety state evaluation in the power plant and the realization of the equipment comprehensive quantitative assessment and early warning of potential failure by mining analysis and modeling massive amounts of real-time data the power equipment. In addition to the foundational technology introduced in this paper, the technology is also verified by the application case in the power supply side remote diagnosis center of Guangdong electric institute.

In today’s big data context, the composition of virtual networks is becoming increasingly complex, so it is neither easy nor difficult to strengthen the control of network security issues. This paper studies the important content of network big data mining-assisted laboratory management. On the basis of discussing the connotation of laboratory safety, combined with management practice, this paper puts forward some suggestions on laboratory safety management. This paper puts forward some views and thoughts on some problems existing in the management and experimental teaching of chemistry laboratory. By judging the stability of instruments and equipment, we know whether the calibration status of instruments and equipment has changed during this period, so as to ensure the sustainable use of instruments and equipment and the accuracy and traceability of laboratory test results. The use of laboratory management system can greatly improve the utilization rate of laboratory equipment, promote students’ autonomous learning, and promote the standardization of laboratory construction. Improve the network monitoring method of big data mining technology and the application mechanism of big data network monitoring, in one type of laboratory. Teachers and students in the laboratory can reasonably arrange their own time according to their own interests to guide and operate experiments. Through continuous operation and practice, students’ practical ability and experimental knowledge level should be improved as much as possible.

Actual importance of study. At the beginning of the 2020s developed world countries and countries which are the leaders of world economic development faced up the challenges of radical structural reformation of social production (from industry to service system) which is based on digitalization. Digital technologies in world science and business practice are considered essential part of a complex technological phenomenon like ‘Industry 4.0’. Digitalization should cover development of all business processes and management processes at micro-, meso- and microlevels, processes of social production management at national and world economy levels. In general, in the 21st century world is shifting rapidly to the strategies of digital technologies application. The countries which introduce these strategies will gain guaranteed competitive advantages: from reducing production costs and improved quality of goods and services to developing new sales market and making guaranteed super-profits. The countries which stand aside from digitalization processes are at risk of being among the outsiders of socio-economic development. Such problem statement highlights the actual importance of determining the directions, trends and strategic priorities of social production digitalization. This issue is really crucial for all world countries, including Ukraine which is in midst of profound structural reformation of all national production system. Problem statement. Digital economy shapes the ground for ‘Industry 4.0’, information, It technologies and large databases become the key technologies. The main asset of ‘Industry 4.0’ is information, the major tool of production is cyberphysical systems that lead to formation the single unified highly productive environmental system of collecting, analyzing and applying data to production and other processes. Cyberphysical systems provides ‘smart machines’ (productive machines, tools and equipment which are programmed) integration via their connection to the Internet, or creation special network, ‘Industrial Internet’ (IIoT) which is regarded as a productive analogue of ‘Internet of Things’ (IoT) that is focused on the consumers. ‘Internet of Things’ can be connected with ‘smart factories’ which use ‘Industrial Internet’ to adjust production processes quickly turning into account the changes in costs and availability of resources as well as demand for production made. One of the most essential tasks for current economics and researchers of systems and processes of organization future maintenance of world production is to determine the main strategic priorities of social production digitalization. Analysis of latest studies and publications. Valuable contribution to the study of the core and directions of strategic priorities concerning social production digitalization was made by such foreign scientists as the Canadian researcher Tapscott D [1], foreigners Sun, L., Zhao, L [2], Mcdowell, M. [3] and others. Yet, the study of issues concerning social production digitalization are mainly done by the team of authors as such issues are complicated and multihierarchical. Furthermore, the problem of social production digitalization is closely linked to the transition to sustainable development, which is reflected in the works by Ukrainian scholars like Khrapkin V., Ustimenko V., Kudrin O., Sagirov A. and others in the monograph “Determinants of sustainable economy development” [4]. The edition of the first in Ukraine inter-disciplinary textbook on Internet economy by a group of scientists like Tatomyr I., Kvasniy L., Poyda S. and others [5] should also be mentioned. But the challenges of social production digitalization are constantly focused on by theoretical scientists, analytics and practitioners of these processes. Determining unexplored parts of general problem. Defining strategic priorities of social production digitalization requires clear understanding of prospective spheres of their application, economic advantages and risks which mass transition of social production from traditional (industrial and post-industrial)to digital technologies bear. A new system of technological equipment (production digitalization, Internet-economy, technology ‘Industry 4.0’, NBIC- technologies and circular economy) has a number of economic advantages for commodity producers and countries, as well as leads to dramatical changes in the whole social security system, changes at labour market and reformation the integral system of social relations in the society. Tasks and objectives of the study. The objective of the study is to highlight the core and define the main strategic priorities of social production digitalization, as they cause the process of radical structural reformation of industrial production, services and social spheres of national economy of world countries and world economy in general. To achieve the objective set in the article the following tasks are determined and solved: - to define the main priorities of digital technologies development, which is radically modify all social production business processes; - to study the essence and the role of circular economy for transition to sustainable development taken EU countries as an example; - to identify the strategic priorities of robotization of production processes and priority spheres of industrial and service robots application; - to define the role of NBIC-technologies in the process of social production structural reformation and its transition to new digital technologies in the 21st century. Method and methodology of the study. While studying strategic priorities of social production digitalization theoretical and empirical methods of study are used, such as historical and logical, analysis and synthesis, abstract and specific, casual (cause-and-effect) ones. All of them helped to keep the track of digital technologies evolution and its impact on structural reformation of social production. Synergetic approach, method of expert estimates and casual methods are applied to ground system influence of digital technologies, ‘Industry 4.0’ and their materialization as ‘circular economy’ on the whole complicated and multihierarchical system of social production in general. Basic material (the results of the study). Digital economy, i.e. economy where it is virtual but not material or physical assets and transactions are of the greatest value, institutional environment in which business processes as well as all managerial processes are developed on the basis of digital computer technologies and information and communication technologies (ICT), lies as the ground for social production digitalization. ICT sphere involves production of electronic equipment, computing, hardware,.software and services. It also provides various information sevices. Information Technology serves as a material basis for digital economy and digital technologies development. Among the basic digital technologies the following ones play the profound role: technology ‘Blockchain’, 3D priniting, unmanned aerial vehicles and flying drones, virtual reality (VR). Augmented reality (AR), Internet of Things (IoT), Industrial Internet of Things (IIoT), Internet of Value (IoV) which is founded on IT and blockchain technology, Internet of Everything (IoE), Artificial Intelligence (AI), neuron networks and robots. These basic digital technologies in business processes and management practices are applied in synergy, complexity and system but not in a single way. System combination of digital technologies gives maximal economic effect from their practical application in all spheres of social production-from industry to all kinds of services. For instance, in education digital technologies promote illustrating and virtual supplement of study materials; in tourism trade they promote engagement of virtual guides, transport and logistics security of tourist routes, virtual adverts and trips arrangements, virtual guidebooks, virtual demonstration of services and IT brochures and leaflets. Digital technologies radically change gambling and show businesses, in particular, they provide virtual games with ‘being there’ effect. Digital technologies drastically modify the retail trade sphere, advertisement and publishing, management and marketing, as well as provide a lot of opportunities for collecting unbiased data concerning changes in market conditions in real time. Digital technologies lie as the basis for ‘circular economy’, whose essence rests with non-linear, secondary, circular use of all existing natural and material resources to provide the production and consumption without loss of quality and availability of goods and services developed on the grounds of innovations, IT-technology application and ‘Industry 4.0’. Among priorities of circular economy potential applications the following ones should be mentioned: municipal services, solid household wastes management and their recycling, mass transition to smart houses and smart towns, circular agriculture development, circular and renewable energy, The potential of circular economy fully and equally corresponds to the demands for energy efficiency and rational consumption of limited natural resources, so it is widely applied in EU countries while transiting to sustainable development. In the 21st century processes of social production robotization draw the maximal attention of the society. There is a division between industrial and service robots which combine artificial intelligence and other various digital technologies in synergy. Industrial robots are widely used in production, including automotive industry, processing industry, energetic, construction sectors and agriculture Services are applied in all other spheres and sectors of national and world economies –from military-industrial complex (for instance, for mining and demining the areas, military drones) to robots-cleaners (robots-vacuum cleaners), robots-taxis, robots engaged in health care service and served as nurses (provide the ill person with water, tidy up, bring meals). Social production robotization is proceeding apace. According to “World Robotic Report 2020”, within 2014 – 2019 the total quantity of industrial robots increased by 85 %. By 2020 in the world the share of robots in the sphere of automated industrial production had comprised 34 %, in electronics – 25%, in metallurgy – 10 %. These indicators are constantly growing which results in structural reformation of the whole system of economic and industrial processes, radical changes in world labour market and the social sphere of world economy in general. Alongside with generally recognized types of digital technologies and robotization processes, an innovation segment of digital economy – NBIC – technologies (Nanotechnology, Biotechnology, Information technology, Cognitive Science) are rapidly spread. Among the priorities of NBIC-technologies development the special place belongs to interaction between information and cognitive technologies. As a material basis for its synergy in NBIC-technologies creation of neuron networks, artificial intelligence, artificial cyber brain for robots are applied. It is estimated as one of the most prospective and important achievements of digital economy which determines basic, innovational vector of social production structural reformations in the 21st century. The sphere of results application. International economic relations and world economy, development of competitive strategies of national and social production digitalization of world economy in general. Conclusions. Digital technologies radically change all spheres of social production and social life, including business and managerial processes at all levels. Digital technologies are constantly developing and modifying, that promotes emergence of new spheres and new business activities and management. 21st century witnessed establishing digital economy, smart economy, circular economy, green economy and other various arrangements of social production which are based on digital technologies. Social production digitalization and innovative digital technologies promotes business with flexible systems of arrangement and management, production and sales grounded on processing large Big Data permanently, on the basis of online monitoring in real time. Grounded on digital technologies business in real time mode processes a massive Big Data and on their results makes smart decisions in all business spheres and business processes management. Radical shifts in social production digitalization provides businesses of the states which in practice introduce digital technologies with significant competitive advantages - from decrease in goods and services production cost to targeted meeting of specific needs of consumers. Whereas, rapid introduction of digital technologies in the countries-leaders of world economic development results in a set of system socio-economic and socio-political challenges, including the following: crucial reformatting the world labour market and rise in mass unemployment, shift from traditional export developing countries’ specialization, breakups of traditional production networks being in force since the end of the 20th century, so called ‘chains of additional value shaping’, breakups of traditional cooperation links among world countries and shaping the new ones based on ‘Industry 4.0’ and ‘Industrial Internet’. Socio-economic and political consequences of radical structural reformation of all spheres in national and world economy in the 21st century, undoubtedly, will be stipulated with the processes of social production digitalization. It will require further systemic and fundamental scientific studies on this complicated and multi hierarchical process.

Study results of quarries and rock-disposal dumps sizes at deposits of non-ferrous metal ores and abandoned deposits have been presented. Operating procedures and mining and conveyor equipment configurations for the mining-engineering recultivation of rock-disposal dumps has been determined. During ecological and mathematical modeling of the applied and author's technology of mining-engineering recultivation, the author's technical rehabilitation approach has been substantiated to significantly reduce the toxic substances emission. It has been proposed to include green sources of electric power supply in mining enterprises energy systems.

Improving the quality of laboratory services must always be improved in improving the quality of the tri dharma of higher education. Good laboratory management is one of the supporting factors, for that reason, the Department of Mining Engineering manages the laboratory. Laboratory management, in this case, is the laboratory equipment inventory system and laboratory control system. This system will be used to carry out monitoring data on the use of website-based laboratory equipment where the use of laboratory equipment must be carried out systematically. The first step is to create a web system for administration and inventory in the laboratory. In this study, in conducting website-based lab management, it is also necessary to map the problems faced by students in relation to services and supporting infrastructure in the laboratory.

Abstract The main task of the maintenance services in hard coal mines is to ensure continuous operation of the equipment (machines). The measurable effect of these actions should be the reduction of maintenance costs of equipment (machinery) and thus the reduction of production costs – coal mining. The paper presents an issue of failure rate of technical measures applied in the mining process. In order to ensure greater efficiency and productivity, it is necessary to find the causes of the most frequent failures in this process and effectively counteract them. As a result of these activities, the production availability of machines/equipment involved in the mining process will increase. This will to a large extent ensure failure-free and uninterrupted progress, increase productivity and improve the quality of manufactured products, as well as reduce the operating costs of equipment (machines), and thus reduce production and product costs. This effect should consist mainly in the control of rational, safe and effective use and operation of equipment (machines) in the exploitation process. An algorithm implemented in one of the hard coal mines was presented. The technical condition of underground mining equipment was observed by periodical measurements of vibration parameters at selected points on the machine – measurements were conducted with a vibration pen. The aim of this research is to improve the reliability of technological process of a mining plant through its failure-free operation. In order to achieve this objective, i.e. the efficiency of a mining company, it is necessary to reduce its costs. The action that leads to this aim is a proper assessment of the technical condition with regard to the equipment used in technological process.

Purpose This paper aims to develop a computer simulation processing method to simulate the mining operation of self-advancing semi-continuous mining technology and optimize the shift step of belt conveyor by using simulation modeling framework based on intelligent objects (SIMIO). The method would effectively solve the challenge of field testing such large-scale equipment. Design/methodology/approach The four operational modes of self-advancing semi-continuous mining technology at single bench had been illustrated. The operational system of this technology was analyzed and broken down to single units. By analyzing the time constitution of one operation cycle, the theoretical optimization model of shift step can be established and the optimization criteria is the time utilization ratio being maximum. Once the simulation flow was determined, a three-dimensional (3D) computer simulation model of this mining technology was developed by adapting the SIMIO simulating software to the theoretical model. The models were run to investigate the outputs from different operational modes using geological and mining data from East open-pit mine. Findings The result of these simulations showed that the four-mining-width one-shift (FMWOS) is at maximum production capacity during all operation modes. If transfer equipment is necessary, then this mode can adapt, but system will become more complex. There are minor differences between two-mining-width one-shift and three-mining-width one-shift. If transfer equipment is not necessary, then the two-mining-width one-shift can adapt during actual production. Originality/value The simulation results show that the proposed method can achieve the optimal shift step of a belt conveyor and effectively reduce the time loss caused by the coordination of multiple pieces of equipment while simultaneously improving operational efficiency.

Background. Technologies applied in geological exploration and mining are undergoing rapid transformations. The scientific progress in this field, which is shifting towards Asia, is characterized by the integration of network and production technologies. The modern society can be conventionally divided into the creative part, i.e. people designing digital technologies, and those operating these technologies. This has become particularly evident with the advancement of the 4th generation of automatics. The period of massive digital transformation started in 2008–2009 with the appearance of the Internet of Things (IoT). This process acquired the term Industry 4.0 or Industrial Internet of Things (IIoT).Aim. To study current digital transformations in drive control technology applied in exploration and mining equipment.Materials and methods. Methods and examples of controlling exploration and mining equipment are presented.Results. The main trends in the development of drive control technology applied in exploration and mining equipment were examined.Conclusion. Modern digital control systems are capable of re-programming controllers using an active or passive identification of multicomponent multiloop controlled objects in real time. The new Flight Contol Language (FCL) designed for programmable controllers incorporates the methods of fuzzy logic [5,8]. This fuzzy control language uses a new type of data — a linguistic variable, which is a numerical variable with a name, e.g. pressure, rotation speed, temperature, etc., involved in linguistic descriptions.

Due all of the challenges faced for feasible mining, new technologies, software, mining equipment, and ore processing are constantly being developed by equipment manufacturers. The focus of this article is to present the premises necessary for the possible applications within the mining industry of the Continuous Surface Miner – a machine currently being used in coal and phosphate mining operations and being evaluated for its incorporation in other diverse mining projects. This article demonstrates the utilization of this equipment in the field of mineral engineering and how a study should be conducted for its application. Continuous Surface Miner compared to the traditional mine equipment, due to the underestimated productivity of the material to be cut demand a higher availability of equipment fleet. The results of the feasibility study show that the use the continuous surface miner did not present itself to be a better option for the mine equipment.

Abstract Artificial intelligence technology is the basic measure to ensure the good operation of electrical automation control system of electromechanical equipment. Because artificial intelligence technology is widely used, it mainly uses auxiliary electrical automation control systems such as data real-time monitoring, data acquisition and data mining in electrical automation control technology of electromechanical equipment. The application of artificial intelligence auxiliary system in electrical automation is mainly data acquisition, which integrates and analyzes the data generated in the production process of electrical automation system equipment. During the operation of the electrical automation system of electromechanical equipment, the data generated is extensive, the amount of calculation is large and the analysis is complex. Once the equipment fault occurs, it is easy to affect the electrical automation system and even the business activities of the enterprise. Therefore, the purpose of applying artificial intelligence technology to the production process of electrical automation system equipment is to centrally process the data parameters entered by electromechanical equipment, so that the accuracy of operating parameters of electrical automation control system of electromechanical equipment can be greatly improved, which is conducive to the stable development of production efficiency.

Gangue and fly ash combined mining technology is the direct filling of the gangue and fly ash to the surface by the feed delivered to the face well, and then filling is in gob areas, while ensuring under the premise of the safe use of surface buildings subjects to the normal maximum level for achieving Coal Mining under the buildings. In the paper, gangue and fly ash on the exploitation of the feed system were designed for filling and compaction equipment, the hydraulic mining was developed on the backfill mining, the conveyor was modified, and the gangue and fly ash mining technology were designed. As the result, the filling rate and surface subsidence was controlled effectively, the service life of the mine was extended, and the good economic and social benefits were achieved.

Traditionally, in any country, mining industry is a strategic sector of the economy, for the development of which a large amount of resources necessary for the production of modern mining equipment, machinery and mechanisms are allocated. In recent years, a steady trend of technical re-equipment of mining enterprises is noted. This measure allows improving labor productivity and increasing the depth of mining due to the modernization of the existing mining equipment and the introduction of the new one; key attention being paid to the quality and reliability of the equipment produced. The current situation of the domestic mining machinery manufacturing market clearly demonstrates a strong dependence on foreign suppliers. In this case, a competent approach to the issues of import substitution in the industry, providing for the development and production of competitive domestic mining equipment that meets all the requirements and expectations of consumers, is urgently needed. As a rule, manufacturers of mining equipment use the entire machinery manufacturing cycle, ranging from blanking and to product assembly. At all stages of manufacturing, it is necessary to follow part processing technology, providing for the assurance of the required surface roughness, surface layer properties and other quality indicators. All this can be provided by a promising method of part processing – tumbling.

In order to solve the problem of aviation equipment system maintenance, it is very difficult to judge the faulty finished product according to the fault phenomenon, the author proposes a data mining-based prediction model for aviation equipment failure finished products. The model takes historical fault record data as input, clusters a large number of fault descriptions through text clustering to obtain fault phenomenon clusters, and establishes a many-to-many relationship between “fault phenomenon” and “fault finished product.” A probability distribution algorithm for faulty finished products is proposed, and by matching new fault phenomena and fault phenomenon clusters, the probability distribution of faulty finished products is calculated. The experimental results show that after calling the model to complete the clustering of the fault information database, 18966 fault phenomenon clusters are obtained, and each fault phenomenon cluster contains 2.9 fault records on average, the many-to-many relationship between the fault phenomenon and the faulty finished product of the fault information database is successfully constructed. The model can effectively predict the probability distribution of products that may fail according to the fault description, and the prediction accuracy can be improved with the increase of the amount of data to meet the actual security needs.

Deep-sea polymetallic nodules are a mineral resource with potential for commercial development. Due to the unique deep-sea environment in which they are found, specialized technology and equipment are required for their extraction. In this paper, firstly, the development of deep-sea polymetallic nodule mining technology is classified into three stages, and its characteristics are summarized. Moreover, the results from research into deep-sea polymetallic nodule mining technology are analyzed, including proposals for mining systems, research into key technologies, basic scientific problems, and proof of technical feasibility from sea tests. Secondly, the testing of the collector prototype and the environmental impact assessment study of Global Sea Mineral Resources NV, as well as the progress of the deep-sea polymetallic nodule mining test project in China, are introduced. On this basis, the opportunities and challenges brought by the fast-growing demand for electric vehicles to the development of deep-sea polymetallic mining technology is analyzed, and a possible technical scheme for a mining system and the trends in its development towards high reliability and high standards of environmental protection according to the requirements of commercial exploitation are explored. This provides a reference for the research and development of high-efficiency technology and equipment for the mining of deep-sea polymetallic nodules.

The procurement of an item in an agency is an activity that is commonly carried out, including in a hospital, particularly the procurement of medical equipment. The procurement of medical equipment at Pengayoman Cipinang Hospital, Jakarta currently still uses the conventional method where the process is still using the manual method, namely by relying on disposable physical items as the main resource and seems to use many procedures that require a long working time. The influx of medical equipment in very large numbers can cause many risks, such as the amount of money it costs to store medical devices and also being vulnerable to the risk of theft. The conditions mentioned above can affect the quality of health services provided by the hospital to patients who should be well preserved. One of the data processing algorithms that is often used in the data mining process is the A algorithm. The benefit is to find trends between one item and another, where more and more medical equipment appears to be used as a reference in the hospital policy process in ensuring the availability of this medical equipment when needed so that the procurement process can always be fulfilled. Based on the results of the research conducted, it was found that the medical equipment that had the most demand was Surgical Ear Loop Masks 3 (58.33%), Non-Sterile Gloves Size M (58.33%), and Surgical Tie-On 3 PLY Masks (100%)

Based on Web of mine equipment maintenance management system,mainly to solve the mining equipment safety inspection,repair and test equipment,the existing problems of mine machinery and equipment maintenance is lack of effective management means information. Based on the introduction of mine equipment maintenance management system using database technology, network technology and the Web,this paper expounds the mine equipment maintenance management system structure,function,design,functions.

Describes the theory and methods of data mining technology, and the latest research progress home and abroad. In the equipment operation of various thermal power plants, more and more field data is stored in the DCS real-time database, and there is always an abundance of knowledge hidden behind the data. Adopting the date mining technology to process and analyze these data can optimize the operation of power plants and provide effective means for monitoring and evaluation of the equipment.

China is the world’s largest coal producer country. However, large-scale coal mining has led to severe environmental pollution issues such as surface subsidence and gangue piling up. The gangue discharging amount has ranked the first in the world and coal mine enterprises are facing enormous discharging reduction pressure. This paper summarizes the research progress of the solid backfilling mining technology and then illustrates the realistic demands and significance of implementing underground coal-waste separation. It also focuses on the technical principles, systems and key equipment of the common underground coal-waste separation methods, such as the selective crushing method, the dense medium shallow groove method, the vibro-assisted jigging method and full-size water separation method and ray identification method. In addition, the selection steps of underground coal-waste separation method, the design process of large section separation chamber and the design principle of separation and backfilling system are proposed, finally, the mining-separating-backfilling + X for coal mining is put forward. By combining the technology of mining-separating-backfilling with other technologies, such as gob-side entry retaining with non-pillar mining, gas extraction, solid waste treatment, water protection mining, mining under buildings, railways and water bodies, the integrated mining methods, mining-separating-backfilling + setting pillars, gas drainage, treatment, protection and prevention methods are formed. It also introduced the ‘mining-separating-backfilling + gas extraction’ technology’s whole idea, system arrangement, separation equipment and practical engineering application effects based on the specific engineering case of pingmei no. 12 coal mine. The results indicate that the integration of underground coal-waste separation and solid backfilling technology could achieve gangue discharging reduction, underground washing and surface subsidence control. It is effective at realizing green mining.