Relevant bibliographies by topics / Mining machinery - Maintenance and repair

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Mining machinery - Maintenance and repair'

Author: Grafiati
Published: 4 June 2021
Last updated: 9 February 2022

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Journal articles on the topic "Mining machinery - Maintenance and repair"

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Andreeva, Liudmila. "Choosing a strategy for mining equipment repair service." Izvestiya vysshikh uchebnykh zavedenii. Gornyi zhurnal, no. 4 (June 25, 2021): 83–91. http://dx.doi.org/10.21440/0536-1028-2021-4-83-91.

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Relevance. The traditional practice of increasing production efficiency with a focus on technical reequipment and increase in the unit capacity of the equipment in operation, carried out without proper changes in the organization of production and for equipment repair service strategy leads to inefficient use of resources and loss of working time, which in turn affects the volume of output of the final product. Research aim is to select the optimal combination of planning strategies for mining equipment repair service. Research methodology includes the methods of structural and functional analysis, scientific generalization, and production experiment. Results. The advantages and disadvantages of planning repairs in the traditional system of planned preventive repairs and maintenance system based on technical diagnostics are presented. The main reasons for the increase in the number of emergency repairs are identified. The main components of effective preparation of repair impacts and methods for calculating the repair cycle on the example of an excavator fleet are given. The results obtained when considering the choice of strategy at one of the mining enterprises in the Urals are presented. Conclusions. To ensure the high performance of mining machinery and equipment during its operation, the effect can be obtained only by using the strategy of “condition-based” repair service with the use of technical diagnostics, condition monitoring of each unit, and repair actions planning that prevent sudden equipment failure.
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Pollard, Jonisha, John Heberger, and Patrick G. Dempsey. "Maintenance and repair injuries in US mining." Journal of Quality in Maintenance Engineering 20, no. 1 (March 4, 2014): 20–31. http://dx.doi.org/10.1108/jqme-02-2013-0008.

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Purpose – The purpose of this paper is to identify key tasks, tools, and equipment associated with maintenance and repair injuries at US mines and to provide some mitigation strategies to reduce these types of injuries. Design/methodology/approach – This study analyzed incidents resulting in injuries reported to the US Mine Safety and Health Administration from 2002 to 2011. Incident reports were limited to those occurring at mining plants, shops, yards, and aboveground locations. Incident reports were analyzed to determine which activities contributed to injuries and were due to machine maintenance and repair, non-powered hand tools, and powered hand tools. An in-depth analysis of the root causes of these injuries was then performed. Findings – Maintenance and repair in mining is associated with a significant number of hand and finger injuries with a range of severities and averaging over 20 amputated fingers, 180 fractured hands and fingers, and 455 hand and finger lacerations per year. Many of these injuries are caused by hands being struck by or caught in tools and equipment. Back and shoulder strains are found to be associated with the most days lost from work and are mostly attributed to materials handling. Practical implications – Occupational injuries and fatalities still occur with high incidences in the mining sector. The mission of the Office of Mine Safety and Health Research (OMSHR; part of the National Institute for Occupational Safety and Health, NIOSH) is to “eliminate mining fatalities, injuries, and illnesses through research and prevention.” As part of this work, OMSHR acquires surveillance data from MSHA to quantify the types and sources of injuries at US mining facilities. The authors evaluated maintenance- and repair-related injuries at US mining sites (excluding underground coal mines). Results of this study suggest a need for improved design of machine guarding, improved hand protection through gloves and equipment design/redesign, and manual materials handling solutions. Originality/value – The findings indicate that maintenance and repair in mining include occupational risks that may be managed through modifications to machines, proper usage of hand tools and hand protection, and improved manual materials handling processes.
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Shishliannikov, Dmitrii I. "Ensuring reliable operation and efficient service of heading and winning machines for potash ore extraction." Izvestiya vysshikh uchebnykh zavedenii Gornyi zhurnal 7, no. 7 (November 11, 2020): 103–9. http://dx.doi.org/10.21440/0536-1028-2020-7-103-109.

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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.
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Tang, Li Fang, and Chuan Jin Wang. "Implementation of Mine Equipment Maintenance Management System Based on Web." Advanced Materials Research 756-759 (September 2013): 1240–43. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.1240.

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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.
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Stefaniak, Pawel, Radosław Zimroz, Walter Bartelmus, and Monika Hardygóra. "Computerised Decision-Making Support System Based on Data Fusion for Machinery System’s Management and Maintenance." Applied Mechanics and Materials 683 (October 2014): 108–13. http://dx.doi.org/10.4028/www.scientific.net/amm.683.108.

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In the present fast-paced world of business in a highly competitive marketplace, the focus on increasing the efficiency of business processes seems to be a reasonable challenge. For this reason in order to optimize production costs, there is an increasing trend toward maximising the use of the operational capabilities of the equipment – technological line components – with the prevention of failure events and their consequences in the form of costly repairs or replacements. A condition-based maintenance (CBM) approach allows to globally monitor, maintain and control operation of the whole complex of equipment and/or processes. The CBM effectively supports decision-making process concerning their further use or determination of the optimum repair/replacement schedule. The presented decision support system is dedicated for an underground copper mine, where the network of belt conveyors is a critical part of the production process. Due to complexity of mechanical system, harsh mining environment and presence of many degradation factors, development of the effective CBM system seems to be justified. It requires the integration of data from different sources, adaptation of advanced data mining techniques, procedures or various diagnostic methods. Because of the multidimensional nature of diagnostic data and diversified technical configurations of the facilities, it was necessary to develop and implement multivariate analytical models based on artificial intelligence techniques. Consequently, it allows to achieve improvement of efficiency of transportation network and reduction of repairs costs and unplanned breakdowns. In this paper we will briefly refer to all these issues.
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IVANOV, Sergey, Polina IVANOVA, and Sergey KUVSHINKIN. "Promising model range career excavators operating time assessment in real operating conditions." Journal of Mining Institute 242 (May 26, 2020): 228. http://dx.doi.org/10.31897/pmi.2020.2.228.

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The development prospects of the mining industry are closely related to the state and development of modern mining machinery and equipment that meet the technical and quality requirements of mining enterprises. Enterprises are focused on a quantitative assessment – the volume of mineral extraction, depending on the functioning efficiency of a promising series of mining machines, which include modern mining excavators. Downtime and unplanned shutdowns of mining excavators directly depend on the operating conditions of the mining machine, which has negative influence on the machine as a whole and its technical condition, which entails a decrease in the efficiency of using expensive mining equipment and economic losses of the mining enterprise. The rationale for external factors that affect the operating time and technical condition of mining excavators is given. For a more detailed assessment of the influence of external influences on the efficiency of operation of mining machines, the influencing factors are divided into two groups: ergatic, directly related to human participation, and factors of a natural-technogenic nature, where human participation is minimized. It was revealed that factors of a natural-technogenic nature have the greatest influence. An algorithm is proposed for a comprehensive assessment of the technical condition and forecasting of operating time both in nominal and in real operating conditions, taking into account factors of a natural and technogenic nature. It is proposed, based on the developed program for planning and evaluating the life of a mining excavator, to adjust the schedules for maintenance and repair (MOT and R) in order to minimize the number of unplanned downtime of a mining excavator and maintain it in good condition.
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Biały, Witold, and Jiri Fries. "Computer Systems Supporting the Management of Machines/Equipment in Hard Coal Mines. Case Study." Management Systems in Production Engineering 27, no. 3 (September 1, 2019): 138–43. http://dx.doi.org/10.1515/mspe-2019-0022.

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AbstractComputer systems supporting the management of machines operation and maintenance in companies have been successfully applied in many branches of industry. Over the last few years these systems have been considerably transformed. It also seems that using them for operating mining machines in hard coal mines is inevitable, as maintenance generates high production costs. If implemented, the systems will allow for optimization of stocks, spare parts and materials, supplies, outsourced services as well as maintenance-repair works. Application of a system supporting the management of mining machines/equipment will also enable a better, more effective use of employees. As a result of these actions, the time needed for preparations and repair will be shortened, which will translate directly into the economic effects of mines.
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Duarte, J., A. Torres Marques, and J. Santos Baptista. "Occupational Accidents Related to Heavy Machinery: A Systematic Review." Safety 7, no. 1 (March 16, 2021): 21. http://dx.doi.org/10.3390/safety7010021.

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Surface and underground mining, due to its technical challenges, is considered a hazardous industry. The great majority of accidents and fatalities are frequently associated with ineffective or inappropriate training methods. Knowing that knowledge of occupational accident causes plays a significant role in safety management systems, it is important to systematise this kind of information. The primary objective of this systematic review was to find evidence of work-related accidents involving machinery and their causes and, thus, to provide relevant data available to improve the mining project (design). The Preferred Reporting of Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement methodology was used to conduct the review. This paper provides the main research results based on a systematic review protocol registered in the International Prospective Register of Systematic Reviews (PROSPERO), where the research strategy, information sources, and eligibility criteria are provided. From the 3071 articles identified, 16 were considered eligible and added to the study. Results are presented in a narrative-based form, with additional data provided in descriptive tables. The data analysed showed that the equipment often related to mining accidents are conveyor belts, haul trucks, and dumpers, especially during maintenance or repair activities. Attention should be paid to powered tools. Effective monitoring and machine operation control are some of the stated measures to minimise accidents. Particular attention should be paid to less experienced and senior workers, mainly through fatigue control, workload management, and appropriate training programs.
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Gerike, Boris L., Boris L. Gerike, Andrey E. Sushko, and Pavel B. Gerike. "INTRODUCTION OF DIGITAL TECHNOLOGIES IN THE FIELD OF TECHNICAL DIAGNOSTICS, MAINTENANCE AND REPAIR OF MINING MACHINERY AND EQUIPMENT." JOURNAL OF MINING AND GEOTECHNICAL ENGINEERING 3, no. 3 (2019): 19–28. http://dx.doi.org/10.26730/2618-7434-2018-3-19-28.

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Khazin, Mark L. "International Emission Standards for Mining Machinery and Equipment." Вестник Пермского национального исследовательского политехнического университета. Геология. Нефтегазовое и горное дело 20, no. 3 (August 2020): 291–300. http://dx.doi.org/10.15593/2712-8008/2020.3.9.

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The paper analyses problems associated with the use of mining machinery equipped with diesel engine releases of exhaust gases that have a harmful impact on human health and the environment. The mining industry uses a wide range of equipment powered by diesel engines: dump trucks, backhoe loaders, drill jumbos and other mining machinery. Engine exhaust gases contain toxic elements that have a significant impact on human health and the environment. Air pollution from gases leads to standbys of mine sites, while a reduced visibility on a route results in a partial or total equipment shutdown. At present, environmental requirements to vehicle engines are a top concern. The problem of air pollution with harmful substances contained in diesel engine exhausts is becoming a global challenge. Solutions of these issues require joint efforts from many countries. International conventions and adoption of relevant standards serve as a means of rapprochement in this sphere. Most operations in Europe, Asia and America are guided by similar standards as to the content of harmful substances in exhaust gases, the European Union being an influencer in this regard by frequently introducing updates and stringent regulations. Other countries are following this trend and revising their emission standards too. European states had paid attention to this issue earlier than other countries. Today, environmental requirements to vehicle engines are a top priority. Research in this field is focused on such issues as increasing productivity of mining machinery engines, reducing labour costs of maintenance and repairs, enhancing fuel efficiency and significantly improving environmental performance.
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Dissertations / Theses on the topic "Mining machinery - Maintenance and repair"

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Gatang'i, Peter Gatheru. "Effective management of machinery in government-operated hospitals." Thesis, Nelson Mandela Metropolitan University, 2010. http://hdl.handle.net/10948/1237.

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The methodology and the processes that are followed in the maintenance of government-operated district hospitals in the Eastern Cape Province of South Africa are outlined while the strategies that are employed to roll-out the maintenance plan have been investigated. The challenges in managing hospital maintenance are identified so that it can be improved and advice be given on the strategies currently being used. The objectives of the research were to determine the effectiveness of machinery maintenance in government-operated district hospitals. The study has been carried out by investigating 50 district hospitals within the Eastern Cape Province, with the aim of obtaining knowledge of practices in relation to the strategic plans and best practices in the maintenance industry. The following factors identified by the maintenance staff were found to be most important in maintenance management practices; realistic budgets, adherence to occupational health and safety regulations, engagement of qualified and skilled maintenance staff, good record management in relation to the equipment under maintenance, availability of tools and materials and keeping abreast with the latest technologies and trends of machinery advancement. The study also revealed that the majority of the hospitals use a combination of in-house and outsourced personnel during maintenance, the outsourced part being under contract from the National Department of Public Works Repair and Maintenance Plan (RAMP) projects. Service kits and recommended replacement parts for machinery are rarely stocked on the hospital premises while only minor spare parts that include replacement bulbs, electrical fittings, plumbing fittings and paint are readily available. In addition, the maintenance staff members have little or no input in maintenance budgeting, this aspect is controlled by hospital management. For maintenance to be effective, strategic planning that takes into account carefully thought-out maintenance management systems is the first step in the direction of setting out definite tangible objectives and goals. The real challenge lies in the implementation and sustainability of the maintenance management system and the monitoring thereof.
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El, Hayek Mustapha Mechanical &amp Manufacturing Engineering Faculty of Engineering UNSW. "Optimizing life-cycle maintenance cost of complex machinery using advanced statistical techniques and simulation." Awarded by:University of New South Wales. School of Mechanical and Manufacturing Engineering, 2006. http://handle.unsw.edu.au/1959.4/24955.

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Maintenance is constantly challenged with increasing productivity by maximizing up-time and reliability while at the same time reducing expenditure and investment. In the last few years it has become evident through the development of maintenance concepts that maintenance is more than just a non-productive support function, it is a profit- generating function. In the past decades, hundreds of models that address maintenance strategy have been presented. The vast majority of those models rely purely on mathematical modeling to describe the maintenance function. Due to the complex nature of the maintenance function, and its complex interaction with other functions, it is almost impossible to accurately model maintenance using mathematical modeling without sacrificing accuracy and validity with unfeasible simplifications and assumptions. Analysis presented as part of this thesis shows that stochastic simulation offers a viable alternative and a powerful technique for tackling maintenance problems. Stochastic simulation is a method of modeling a system or process (on a computer) based on random events generated by the software so that system performance can be evaluated without experimenting or interfering with the actual system. The methodology developed as part of this thesis addresses most of the shortcomings found in literature, specifically by allowing the modeling of most of the complexities of an advanced maintenance system, such as one that is employed in the airline industry. This technique also allows sensitivity analysis to be carried out resulting in an understanding of how critical variables may affect the maintenance and asset management decision-making process. In many heavy industries (e.g. airline maintenance) where high utilization is essential for the success of the organization, subsystems are often of a rotable nature, i.e. they rotate among different systems throughout their life-cycle. This causes a system to be composed of a number of subsystems of different ages, and therefore different reliability characteristics. This makes it difficult for analysts to estimate its reliability behavior, and therefore may result in a less-than-optimal maintenance plan. Traditional reliability models are based on detailed statistical analysis of individual component failures. For complex machinery, especially involving many rotable parts, such analyses are difficult and time consuming. In this work, a model is proposed that combines the well-established Weibull method with discrete simulation to estimate the reliability of complex machinery with rotable subsystems or modules. Each module is characterized by an empirically derived failure distribution. The simulation model consists of a number of stages including operational up-time, maintenance down-time and a user-interface allowing decisions on maintenance and replacement strategies as well as inventory levels and logistics. This enables the optimization of a maintenance plan by comparing different maintenance and removal policies using the Cost per Unit Time (CPUT) measure as the decision variable. Five different removal strategies were tested. These include: On-failure replacements, block replacements, time-based replacements, condition-based replacements and a combination of time-based and condition-based strategies. Initial analyses performed on aircraft gas-turbine data yielded an optimal combination of modules out of a pool of multiple spares, resulting in an increased machine up-time of 16%. In addition, it was shown that condition-based replacement is a cost-effective strategy; however, it was noted that the combination of time and condition-based strategy can produce slightly better results. Furthermore, a sensitivity analysis was performed to optimize decision variables (module soft-time), and to provide an insight to the level of accuracy with which it has to be estimated. It is imperative as part of the overall reliability and life-cycle cost program to focus not only on reducing levels of unplanned (i.e. breakdown) maintenance through preventive and predictive maintenance tasks, but also optimizing inventory of spare parts management, sometimes called float hardware. It is well known that the unavailability of a spare part may result in loss of revenue, which is associated with an increase in system downtime. On the other hand increasing the number of spares will lead to an increase in capital investment and holding cost. The results obtained from the simulation model were used in a discounted NPV (Net Present Value) analysis to determine the optimal number of spare engines. The benefits of this methodology are that it is capable of providing reliability trends and forecasts in a short time frame and based on available data. In addition, it takes into account the rotable nature of many components by tracking the life and service history of individual parts and allowing the user to simulate different combinations of rotables, operating scenarios, and replacement strategies. It is also capable of optimizing stock and spares levels as well as other related key parameters like the average waiting time, unavailability cost, and the number of maintenance events that result in extensive durations due to the unavailability of spare parts. Importantly, as more data becomes available or as greater accuracy is demanded, the model or database can be updated or expanded, thereby approaching the results obtainable by pure statistical reliability analysis.
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Conrad, George R. "Development of course outlines for a maintenance technician training program." CSUSB ScholarWorks, 1985. https://scholarworks.lib.csusb.edu/etd-project/415.

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Elwany, Alaa H. "Sensor-based prognostics and structured maintenance policies for components with complex degradation." Diss., Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/37198.

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We propose a mathematical framework that integrates low-level sensory signals from monitoring engineering systems and their components with high-level decision models for maintenance optimization. Our objective is to derive optimal adaptive maintenance strategies that capitalize on condition monitoring information to update maintenance actions based upon the current state of health of the system. We refer to this sensor-based decision methodology as "sense-and-respond logistics". As a first step, we develop and extend degradation models to compute and periodically update the remaining life distribution of fielded components using in situ degradation signals. Next, we integrate these sensory updated remaining life distributions with maintenance decision models to; (1) determine, in real-time, the optimal time to replace a component such that the lost opportunity costs due to early replacements are minimized and system utilization is increased, and (2) sequentially determine the optimal time to order a spare part such that inventory holding costs are minimized while preventing stock outs. Lastly, we integrate the proposed degradation model with Markov process models to derive structured replacement and spare parts ordering policies. In particular, we show that the optimal maintenance policy for our problem setting is a monotonically non-decreasing control limit type policy. We validate our methodology using real-world data from monitoring a piece of rotating machinery using vibration accelerometers. We also demonstrate that the proposed sense-and-respond decision methodology results in better decisions and reduced costs compared to other traditional approaches.
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Saxena, Abhinav. "Knowledge-Based Architecture for Integrated Condition Based Maintenance of Engineering Systems." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/16125.

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A paradigm shift is emerging in system reliability and maintainability. The military and industrial sectors are moving away from the traditional breakdown and scheduled maintenance to adopt concepts referred to as Condition Based Maintenance (CBM) and Prognostic Health Management (PHM). In addition to signal processing and subsequent diagnostic and prognostic algorithms these new technologies involve storage of large volumes of both quantitative and qualitative information to carry out maintenance tasks effectively. This not only requires research and development in advanced technologies but also the means to store, organize and access this knowledge in a timely and efficient fashion. Knowledge-based expert systems have been shown to possess capabilities to manage vast amounts of knowledge, but an intelligent systems approach calls for attributes like learning and adaptation in building autonomous decision support systems. This research presents an integrated knowledge-based approach to diagnostic reasoning for CBM of engineering systems. A two level diagnosis scheme has been conceptualized in which first a fault is hypothesized using the observational symptoms from the system and then a more specific diagnostic test is carried out using only the relevant sensor measurements to confirm the hypothesis. Utilizing the qualitative (textual) information obtained from these systems in combination with quantitative (sensory) information reduces the computational burden by carrying out a more informed testing. An Industrial Language Processing (ILP) technique has been developed for processing textual information from industrial systems. Compared to other automated methods that are computationally expensive, this technique manipulates standardized language messages by taking advantage of their semi-structured nature and domain limited vocabulary in a tractable manner. A Dynamic Case-based reasoning (DCBR) framework provides a hybrid platform for diagnostic reasoning and an integration mechanism for the operational infrastructure of an autonomous Decision Support System (DSS) for CBM. This integration involves data gathering, information extraction procedures, and real-time reasoning frameworks to facilitate the strategies and maintenance of critical systems. As a step further towards autonomy, DCBR builds on a self-evolving knowledgebase that learns from its performance feedback and reorganizes itself to deal with non-stationary environments. A unique Human-in-the-Loop Learning (HITLL) approach has been adopted to incorporate human feedback in the traditional Reinforcement Learning (RL) algorithm.
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Klopper, Marthinus Ferreira. "The life expectancy of heavy earthmoving equipment on a sand dune mine in a highly corrosive environment." Thesis, Stellenbosch : Stellenbosch University, 2004. http://hdl.handle.net/10019.1/80762.

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Thesis (MBA)--Stellenbosch University, 2004.
ENGLISH ABSTRACT: Richards Bay Minerals (RBM) went through a restructuring process in 2002. The effect that these changes had on the life expectancy of the heavy earthmoving equipment (HEME) at the company’s sand dune mining operation situated at Richard’s Bay on the north coast of KwaZulu-Natal, was unknown. This study explores these, and various other factors, that influence the life expectancy of the HEME in this highly corrosive environment. During the last number of years there has been no equipment replacement philosophy at RBM and this has resulted in the average age of HEME at the mine being extremely high. This study suggests that when restructuring is implemented in the wrong way, the process can have significant negative implications. The study determines how the behaviour of especially drivers and maintenance personnel (maintainers) impacts on the expected life of the HEME at RBM. The hidden cost element of driver and maintainer unhappiness, however, is not included as part of this study. In the first part of this study project, the writer focuses on what may have caused the unhappiness, and makes suggestions for further studies aimed at addressing this unhappiness and changing the behaviour of drivers and maintainers. These suggestions should be seen as guidelines, as measures that work in one company may not necessarily work in another. The second part of the study project deals with the replacement philosophy regarding HEME at RBM. The mine has various types of equipment, but the main focus of this research falls on the following: Caterpillar 966- 980 (payloaders), track type equipment Caterpillar D7R/H (dozers), Caterpillar 988- 992 (heavy duty payloaders) and Bell B25 articulated dumptrucks (dumptrucks) Four different replacement models are investigated and discussed in detail. The model that was best aligned with the Caterpillar proposed best replacement practice, as stipulated by the Caterpillar replacement expert, is identified. Finally, a replacement cycle for the different types of equipment is proposed.
AFRIKAANSE OPSOMMING: Richardsbaai Minerale (RBM) het in 2002 deur ‘n herstruktureringsprogram gegaan. Die uitwerking wat die gevolge daarvan op die swaar grondverskuiwingsvoertuie (SGV) gehad het was onbekend. Gedurende die laaste aantal jare was daar geen vervangingsbeleid by RBM nie, en dit het meegebring dat die gemiddelde ouderdom van die SGV op die myn buitengewoon hoog is. Dit is belangrik om te bepaal wat die invloed van menslike gedrag van veral die drywers en herstelpersoneel op die verwagte leeftyd van SGV is. Die versteekte koste wat verbind word met ongelukkige drywers en herstelpersoneel maak nie deel uit van hierdie studie nie. As herstrukturering op die verkeerde manier toegepas word kan dit ‘n negatiewe impak hê. In die studie sal daar aandag gegee word aan wat die negatiewe elemente is en wat is die moontlike oorsaak daarvan. Daar word ook sekere voorstelle gemaak vir toekomstige studies om die ongelukkigheid aan te spreek en ‘n gedragsverandering na vore te bring. Die voorstelle is slegs riglyne en, wat in een maatskappy werk sal nie noodwendig in ‘n ander een werk nie. Die tweede deel van die werkstuk fokus op vervangingsteorieë met betrekking tot die SGV op RBM. Die myn het verskeie tipes SGVs maar die fokus het geval op vier soorte SGV. Hulle is Caterpillar 966- Caterpillar 980 (gemiddelde laaiers), spoor tipe toerusting Caterpillar D7R/H (stootskrapers), Caterpillar 988- Caterpillar 992 (swaargewig mobiele laaiers) en Bell B25 geartikuleerde stortings trokke (stortings trokke). Vier verskillende modelle is ondersoek en deeglik bespreek. Die model met die beste uitslae wat die mas opgekom het ten opsigte van die Caterpillar se voorgestelde beste vervangings praktyk, soos aangedui deur die Caterpillar voertuig vervangings kenner, is ge-identifiseer. Laastens word die vervangingsiklus vir die verskillende tipes toerusting voorgestel.
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Skálová, Hana. "Návrhy na zlepšení hospodaření s dlouhodobým hmotným majetkem." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2012. http://www.nusl.cz/ntk/nusl-223653.

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This thesis is focused on analysis of production facilities utilization and maintenance in the company RAMET C.H.M. a.s. located in Kunovice. In this thesis, there is performed the analysis of present property condition, machinery and equipment used within radar antenna production. Within property maintenance, there are introduced planned and unplanned processes of servicing activities and machine and equipment repair. In a part of proposal for solution, there are recommended processes for keeping up production capabilities based on extensive analysis of size property influence on production volume. The method for reliability estimation of production chain is described for the antenna production, related to limiting production capability and costs to maintain service availability of production facilities.
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Cao, Qiushi. "Semantic technologies for the modeling of predictive maintenance for a SME network in the framework of industry 4.0 Smart condition monitoring for industry 4.0 manufacturing processes: an ontology-based approach Using rule quality measures for rule base refinement in knowledge-based predictive maintenance systems Combining chronicle mining and semantics for predictive maintenance in manufacturing processes." Thesis, Normandie, 2020. http://www.theses.fr/2020NORMIR04.

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Dans le domaine de la fabrication, la détection d’anomalies telles que les défauts et les défaillances mécaniques permet de lancer des tâches de maintenance prédictive, qui visent à prévoir les défauts, les erreurs et les défaillances futurs et à permettre des actions de maintenance. Avec la tendance de l’industrie 4.0, les tâches de maintenance prédictive bénéficient de technologies avancées telles que les systèmes cyberphysiques (CPS), l’Internet des objets (IoT) et l’informatique dématérialisée (cloud computing). Ces technologies avancées permettent la collecte et le traitement de données de capteurs qui contiennent des mesures de signaux physiques de machines, tels que la température, la tension et les vibrations. Cependant, en raison de la nature hétérogène des données industrielles, les connaissances extraites des données industrielles sont parfois présentées dans une structure complexe. Des méthodes formelles de représentation des connaissances sont donc nécessaires pour faciliter la compréhension et l’exploitation des connaissances. En outre, comme les CPSs sont de plus en plus axées sur la connaissance, une représentation uniforme de la connaissance des ressources physiques et des capacités de raisonnement pour les tâches analytiques est nécessaire pour automatiser les processus de prise de décision dans les CPSs. Ces problèmes constituent des obstacles pour les opérateurs de machines qui doivent effectuer des opérations de maintenance appropriées. Pour relever les défis susmentionnés, nous proposons dans cette thèse une nouvelle approche sémantique pour faciliter les tâches de maintenance prédictive dans les processus de fabrication. En particulier, nous proposons quatre contributions principales: i) un cadre ontologique à trois niveaux qui est l’élément central d’un système de maintenance prédictive basé sur la connaissance; ii) une nouvelle approche sémantique hybride pour automatiser les tâches de prédiction des pannes de machines, qui est basée sur l’utilisation combinée de chroniques (un type plus descriptif de modèles séquentiels) et de technologies sémantiques; iii) a new approach that uses clustering methods with Semantic Web Rule Language (SWRL) rules to assess failures according to their criticality levels; iv) une nouvelle approche d’affinement de la base de règles qui utilise des mesures de qualité des règles comme références pour affiner une base de règles dans un système de maintenance prédictive basé sur la connaissance. Ces approches ont été validées sur des ensembles de données réelles et synthétiques
In the manufacturing domain, the detection of anomalies such as mechanical faults and failures enables the launching of predictive maintenance tasks, which aim to predict future faults, errors, and failures and also enable maintenance actions. With the trend of Industry 4.0, predictive maintenance tasks are benefiting from advanced technologies such as Cyber-Physical Systems (CPS), the Internet of Things (IoT), and Cloud Computing. These advanced technologies enable the collection and processing of sensor data that contain measurements of physical signals of machinery, such as temperature, voltage, and vibration. However, due to the heterogeneous nature of industrial data, sometimes the knowledge extracted from industrial data is presented in a complex structure. Therefore formal knowledge representation methods are required to facilitate the understanding and exploitation of the knowledge. Furthermore, as the CPSs are becoming more and more knowledge-intensive, uniform knowledge representation of physical resources and reasoning capabilities for analytic tasks are needed to automate the decision-making processes in CPSs. These issues bring obstacles to machine operators to perform appropriate maintenance actions. To address the aforementioned challenges, in this thesis, we propose a novel semantic approach to facilitate predictive maintenance tasks in manufacturing processes. In particular, we propose four main contributions: i) a three-layered ontological framework that is the core component of a knowledge-based predictive maintenance system; ii) a novel hybrid semantic approach to automate machinery failure prediction tasks, which is based on the combined use of chronicles (a more descriptive type of sequential patterns) and semantic technologies; iii) a new approach that uses clustering methods with Semantic Web Rule Language (SWRL) rules to assess failures according to their criticality levels; iv) a novel rule base refinement approach that uses rule quality measures as references to refine a rule base within a knowledge-based predictive maintenance system. These approaches have been validated on both real-world and synthetic data sets
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Chaloupková, Veronika. "Návrhy na zlepšení hospodaření s dlouhodobým hmotným majetkem." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2017. http://www.nusl.cz/ntk/nusl-319433.

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This Master thesis deals with the management of long-term tangible property in the company Česko-slezská výrobní, a. s., which is engaged in manufacturing of portable and sanitary cabins. The thesis is divided into three parts. The first part describes the theoretical background, which forms the theoretical base of the whole thesis. The second part is focused on analysis of the current situation of long-term tangible property in the company and property maintenance. The result of the analysis is identification of weaknesses and opportunities for development. In the last part are proposed solution including economic evaluation and time-consuming.
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Leme, Murilo Oliveira. "Metodologia de manutenção preditiva para motores elétricos baseada em monitoramento de variáveis físicas e análise multicritério." Universidade Tecnológica Federal do Paraná, 2017. http://repositorio.utfpr.edu.br/jspui/handle/1/2905.

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Este trabalho apresenta o desenvolvimento de uma metodologia de manutenção preditiva para motores elétricos, que utiliza a técnica de monitoramento de variáveis, transmissão de dados pela rede elétrica (Powerline Communication) e um tratamento com os métodos multicritério para classificação (ELECTRE TRI e AHPSort) e ordenação (ELECTRE II) dos motores que apresentam condição de falha incipiente, além do aproveitamento das instalações elétricas existentes para a aquisição de dados do funcionamento de motores elétricos tais como: tensão, corrente, temperatura e vibração. Essas informações podem ser avaliadas e tratadas através de métodos multicritério para alocar os motores em classes que representam estados de funcionamento normal, aceitável e falha incipiente. Assim, nos motores classificados em condição de falha incipiente pode ser realizado um ranking para apontar o motor em pior estado de funcionamento. Neste trabalho, foi conduzido um ensaio de falhas programadas em bancada com um período de aquisição de 1 minuto das variáveis de funcionamento de seis motores. Neste período, pode ser feito o registro do motor que apresentou as condições mais críticas para a falha, considerando as variáveis medidas como critérios na análise. Após um largo período de análise, foram computadas todas as vezes que cada motor foi classificado na classe de falha incipiente e ranqueado em primeiro lugar, significando que ele possui condições fora do padrão normal de funcionamento e piores que dos outros motores analisados. Com isso, foi possível identificar o motor que, por mais vezes, esteve em condição de falha incipiente, refletindo as falhas inseridas durante o ensaio. Essa metodologia possibilitou indicar ao gestor da manutenção, os desvios do funcionamento normal de motores elétricos, considerando mais de uma variável ao mesmo tempo, alinhado aos objetivos do decisor, através dos pesos calculados para os critérios, limites e preferências estabelecidas em cada método multicritério utilizado na metodologia proposta neste trabalho.
This work presents the development of a predictive maintenance methodology for electric motors, which uses the variable monitoring technique, data transmission through the electric network (Powerline Communication) and a treatment with multicriteria methods for sorting (ELECTRE TRI and AHPSort) and ranking (ELECTRE II) electric motors with incipient failure condition and the use of existing electrical installations for the acquisition of data of the operation of electric motors such as voltage, current, temperature and vibration. This information can be evaluated and treated through multicriteria methods to allocate motors in classes that represent normal, acceptable, and incipient failure states. Thus, in electric motors classified as incipient failure condition, a ranking can be performed to detect the engine in the worst operating state. In this work, a bench experiment was conducted with a 1-minute acquisition period of the operating variables in 6 motors. In this period, the electric motor can be registered that presented the most critical conditions for the fault, considering the measured variables as criteria in the analysis. After a longer period of analysis, we computed every time this engine was classified in the incipiente failure and first rank class, which means that it has conditions that are out of the normal operating range and worse than the other engines analyzed. Through this methodology it is possible to indicate to the maintenance manager deviations from the normal operation of electric motors, considering more than one variable at the same time aligned to the objectives of the decision maker, through the weights calculated for the criteria and limits and preferences established in each multicriteria method used in the methodology proposed in this work.
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Books on the topic "Mining machinery - Maintenance and repair"

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Chekavskiĭ, V. I. Organizat͡s︡ii͡a︡ ėkspluatat͡s︡ii i kapitalʹnogo remonta gorno-shakhtnogo oborudovanii͡a︡. Moskva: "Nedra", 1985.

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S, Dhillon B. Mining equipment reliability, maintainability, and safety. London: Springer, 2008.

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Krulʹkevich, M. I. Soderzhanie i remont gornykh vyrabotok ugolʹnykh shakht. Kiew: "Tėkhnika", 1988.

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Tomlingson, Paul D. Equipment management: Key to equipment reliability and productivity in mining. 2nd ed. Littleton, Colo., USA: Society for Minig, Metallurgy, and Exploration, 2010.

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Tomlingson, Paul D. Equipment management: Key to equipment reliability and productivity in mining. 2nd ed. Littleton, Colo., USA: Society for Minig, Metallurgy, and Exploration, 2010.

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editor, Cui Fenglu, ed. Mei kuang jing xia shi yong dian qi ji shu ji gu zhang chu li. Beijing Shi: Mei kuang gong ye chu ban she, 2012.

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Belʹfor, V. E. Avtomatizat͡s︡ii͡a︡ upravlenii͡a︡ remontom oborudovanii͡a︡ na gornykh predprii͡a︡tii͡a︡kh. Moskva: "Nedra", 1986.

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Robin, Burgess-Limerick, and Steiner Lisa J, eds. Human factors for the design, operation, and maintenance of mining equipment. Boca Raton: Taylor & Francis, 2010.

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Kuenzi, Joan K. Mobile mine equipment maintenance safety: A review of U.S. Bureau of Mines research. [Washignton, DC]: U.S. Dept. of the Interior, Bureau of Mines, 1995.

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Bloch, Heinz P. Machinery component maintenance and repair. Houston: Gulf Pub. Co., Book Division, 1985.

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Book chapters on the topic "Mining machinery - Maintenance and repair"

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Smith, Ricky, and R. Keith Mobley. "Maintenance Welding." In Industrial Machinery Repair, 460–538. Elsevier, 2003. http://dx.doi.org/10.1016/b978-075067621-2/50024-x.

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Smith, Ricky, and R. Keith Mobley. "Maintenance Skills Assessment." In Industrial Machinery Repair, 26–49. Elsevier, 2003. http://dx.doi.org/10.1016/b978-075067621-2/50003-2.

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Bloch, Heinz P., and Fred K. Geitner. "Machinery alignment." In Machinery Component Maintenance and Repair, 205–63. Elsevier, 2019. http://dx.doi.org/10.1016/b978-0-12-818729-6.00005-8.

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Smith, Ricky, and R. Keith Mobley. "Fundamental Requirements of Effective Preventive/Predictive Maintenance." In Industrial Machinery Repair, 10–25. Elsevier, 2003. http://dx.doi.org/10.1016/b978-075067621-2/50002-0.

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Bloch, Heinz P., and Fred K. Geitner. "Machinery maintenance: An overview." In Machinery Component Maintenance and Repair, 3–12. Elsevier, 2019. http://dx.doi.org/10.1016/b978-0-12-818729-6.00001-0.

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"Machinery Maintenance: An Overview." In Machinery Component Maintenance and Repair, 3–10. Elsevier, 2005. http://dx.doi.org/10.1016/s1874-6942(05)80016-1.

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Bloch, Heinz P., and Fred K. Geitner. "Process machinery piping." In Machinery Component Maintenance and Repair, 153–201. Elsevier, 2019. http://dx.doi.org/10.1016/b978-0-12-818729-6.00004-6.

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Bloch, Heinz P., and Fred K. Geitner. "Machinery foundations and grouting." In Machinery Component Maintenance and Repair, 69–152. Elsevier, 2019. http://dx.doi.org/10.1016/b978-0-12-818729-6.00003-4.

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Bloch, Heinz P., and Fred K. Geitner. "Balancing of machinery components." In Machinery Component Maintenance and Repair, 265–367. Elsevier, 2019. http://dx.doi.org/10.1016/b978-0-12-818729-6.00006-x.

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Bloch, Heinz P., and Fred K. Geitner. "Centrifugal compressor rotor repair." In Machinery Component Maintenance and Repair, 519–50. Elsevier, 2019. http://dx.doi.org/10.1016/b978-0-12-818729-6.00009-5.

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Conference papers on the topic "Mining machinery - Maintenance and repair"

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Karlstetter, Roman, Robert Widhopf-Fenk, Jakob Hermann, Driek Rouwenhorst, Amir Raoofy, Carsten Trinitis, and Martin Schulz. "Turning Dynamic Sensor Measurements From Gas Turbines Into Insights: A Big Data Approach." In ASME Turbo Expo 2019: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/gt2019-91259.

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Abstract Gas turbine power plants generate an ever growing amount of high frequency dynamic sensor data. One of the applications of this data is the protection against problems induced by combustion dynamics, as, e.g., with the ArgusOMDS system developed by IfTA. In the light of digitalization, this data has the potential to also be used in other areas and ultimately transform maintenance, repair and overhaul approaches. However, current solutions are not designed to cope with the large time windows needed for a general analysis and this can hinder development of advanced machine analysis algorithms. In this work, we present an end-to-end approach for large scale sensor measurement analysis, employing data mining techniques and enabling machine learning algorithms. Our approach covers the complete data pipeline from sensor measurement acquisition to analysis and visualization. We demonstrate the feasibility of our approach by presenting several case studies that prove the benefits over existing solutions.
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Skokov, E. V., V. V. Ladoshko, and M. I. CHastukhin. "Repair and maintenance of agricultural machinery with departure." In ТЕНДЕНЦИИ РАЗВИТИЯ НАУКИ И ОБРАЗОВАНИЯ. НИЦ «Л-Журнал», 2018. http://dx.doi.org/10.18411/lj-05-2018-68.

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HOSEINIE, SEYED HADI, BEHZAD GHODRATI, and DIEGO GALAR. "Smart Maintenance Solutions for Automated Mining Machinery." In Third International Conference on Advances in Mechanical and Automation Engineering - MAE 2015. Institute of Research Engineers and Doctors, 2015. http://dx.doi.org/10.15224/978-1-63248-080-4-110.

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Castilla, Javier. "PREDICTIVE MAINTENANCE OF MINING MACHINERY BASED ON VIBRATIONAL ANALYSIS." In 18th International Multidisciplinary Scientific GeoConference SGEM2018. Stef92 Technology, 2018. http://dx.doi.org/10.5593/sgem2018/1.3/s03.084.

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Vahed, Amir Taghizadeh, Behzad Ghodrati, Nuray Demirel, and Morteza Hosseini Yazdi. "Predictive Maintenance of Mining Machinery Using Machine Learning Approaches." In Proceedings of the 29th European Safety and Reliability Conference (ESREL). Singapore: Research Publishing Services, 2019. http://dx.doi.org/10.3850/978-981-11-2724-3_0756-cd.

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Meseroll, Robert J., Christopher J. Kirkos, and Russell A. Shannon. "Data mining navy flight and maintenance data to affect repair." In 2007 IEEE Autotestcon. IEEE, 2007. http://dx.doi.org/10.1109/autest.2007.4374256.

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Tiina E A Mattila, Kim O Kaustell, and Risto H Rautiainen. "Analysis of Safety Intervention Bottlenecks in Maintenance and Repair of Farm Machinery and Buildings." In 2009 Reno, Nevada, June 21 - June 24, 2009. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2009. http://dx.doi.org/10.13031/2013.27181.

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Zhang, Qinghua, Xiaodan Lv, and Juan Shi. "Research on inventory sharing model of frequent mining machinery maintenance spare parts." In 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA). IEEE, 2017. http://dx.doi.org/10.1109/iciea.2017.8283026.

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Hu, Yaoguang, Zhengjie Guo, Jingqian Wen, and Jialin Han. "Research on knowledge mining for agricultural machinery maintenance based on association rules." In 2015 IEEE 10th Conference on Industrial Electronics and Applications (ICIEA). IEEE, 2015. http://dx.doi.org/10.1109/iciea.2015.7334235.

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Gu, Qingsong. "Fault analysis and maintenance of the hydraulic system of coal mining machinery." In 2017 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017). Paris, France: Atlantis Press, 2017. http://dx.doi.org/10.2991/icmmct-17.2017.3.

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