Mining equipment maintenance and reliability: a systematic review of modelling approaches, solution methods, and applications

Introduction Introductory Mathematical Concepts for Mining Equipment Reliability, Maintainability, and Safety Analysis Introduction to Reliability, Maintainability, and Safety Mining Equipment Reliability Human Factors and Error in Mining Mining Equipment Maintainability Mining Equipment Reliability and Maintainability Testing Mining Equipment Maintenance Mining Equipment Costing Introduction to Mining Equipment Safety Programmable Electronic Mining System Safety

PT.Leighton Contarctors Indonesia is one of the mining companies engaged in the repair and maintenance of mining equipment. The current system is still using the old method of recording equipment damage every day still rely on reports from operational supervisors or operators who directly report the damage via HT radio (Hand Talk) so not infrequently the information collided with other information because very much users and make inaccurate data damage information and often cause errors in analyzing the damage to the conveyance equipment. In order to facilitate the smooth operation of operations in processing data repair and maintenance of mining equipment then PT.Leighton Contractors Indonesia to make an application using Borland Delphi 7 programming language using the MySQL database on Xampp. With the application is expected to facilitate the smooth operation of the company's operations in processing data repair and maintenance of mining equipment, and accelerate in obtaining information damage, repair and maintenance of mining equipment on every day. Keywords : Ap plication , repair and maintenance , mining equipment , Delphi 7

In the rapid economic development today, accelerating coal mining to ensure energy supply is an important guarantee for the healthy and stable development of the economy. Compared with underground mining, open-pit coal mine is of relatively low technical difficulty and mining cost. Through high-efficient, environment-friendly and energy-saving green mining of large complete sets of equipment, open-pit coal resources can be fully utilized. In order to improve the efficiency of open-pit coal mining, this paper studies the application of information technology in the management and maintenance of mining equipment in large open-pit mines. This paper builds an intelligent control model based on the study on strengthening the intellectualization of the complete set of semi-continuous mining equipment of 10,000-ton open-pit coal mine, so as to improve the operation efficiency and safety of the semi-continuous mining equipment of 10,000-ton open-pit coal mine through automatic detection, monitoring, protection and control of the mining equipment. The results show that the equipment management efficiency is improved by 42.12% after using the intelligent control model. This is conducive to improving the management efficiency and maintenance of mining equipment.

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.

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.

Digital twin technology is a real-time simulation skill based on computer models and real physical systems. Digital twin for extractive equipment combines physical equipment with virtual models to achieve comprehensive monitoring, prediction and optimization of extractive equipment and its operational status through data integration, simulation and analysis. The key elements of extractive equipment digital twin include sensor and data acquisition, physical model building, model calibration and validation, data analysis and decision support. By collecting the sensor data of the equipment, Efficacy of virtual environments in developing collaboration strategies between industrial robots and humans including parameters such as temperature, vibration, pressure, etc., and then the corresponding digital twin models can be established. These models can be calibrated and verified based on actual data to ensure their accuracy and reliability. Applications of digital twins for extractive equipment include operational status monitoring and prediction, optimization of operation and maintenance strategies, training and knowledge management. Digital twins can also record equipment operation data and fault information to form a knowledge base for subsequent fault diagnosis and decision-making. The application of digital twin technology for mining equipment can improve the efficiency and reliability of mining equipment, reduce operating costs, and help improve the technical level and training of employees.

Looks at the use of lubrication in the maintenance of mining equipment through the examination of five case studies of mines from different areas and their consumption of lube oil. Concludes that a suitable management of lubricant consumption plays an important role in production costs and optimization.

Introduction. The value of resources is becoming increasingly important to mining proprietors, since the maintenance of mining equipment is quite expensive. Increased scope and cost of repairs are largely determined by the quality of mining machines and equipment operation in production environment, as well as by their reliability and maintainability. The costs of preventive maintenance are over the limit by 40–50%, in most instances, due to equipment shutdowns caused by subsystem failures. Components with hidden defects as well as the methods of components reconditioning that do not ensure long-term operation cause a significant overrun of costs for breakdown maintenance. The quality of mining equipment maintenance is in direct relationship with the effective methods of components reconditioning, including the methods of components hardening both during their manufacture at machinebuilding plants and during their repairs at repair works that carry out complex, mainly major repairs of mining equipment. Adherence to the flow process of reconditioning/hardening of the component surface in contact with another component is of great importance. Therefore, to preserve fixed assets, in particular, mining and transport equipment, it is essential to find that reconditioning methods which allow to preserve consumer properties and operability of equipment for a sufficiently long time. Subject matter. The article provides an overview of methods of mining machine components reconditioning/hardening involving concentrated energy fluxes. In the authors’ opinion, these are the most effective methods to increase the resource and reliability of mining machine components by 2–3 times. The choice of components reconditioning/hardening method depends entirely on the service centre capacities, necessary technological equipment availability, personnel qualifications and, most importantly, economic feasibility of using a particular method of reconditioning/hardening. Research objective is to consider the most effective methods of mining machine components reconditioning/hardening. Methods of research include the interpretation of a number of experiments conducted at mining enterprises to obtain comparative characteristics of the most effective methods of mining machine components reconditioning/hardening. Research results. The most effective methods of components reconditioning/hardening are identified and recommended practices are provided. Conclusions. It has been established that the application of a particular components reconditioning/hardening method should be based on the data from tribological maps, as well as necessary equipment availability and economic feasibility.

Maintenance is an important element of mining equipment life cycle. The chapter presents various important aspects of mining equipment maintenance including maintenance-related facts and figures, factors contributing to equipment maintenance cost in mines, maintenance of explosion protected switchgear in mines, useful maintenance measures for mines, and mathematical models for performing mining equipment maintenance.KeywordsPreventive MaintenanceMaintenance ActivityMining SystemPeriodic MaintenanceIndex ParameterThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

In the mineral industries, the heavy equipment is widely used, and the operator performance is a significant factor for fulfilling intended functions of this equipment. This study aims to analyse and interpret the effect of the human factor on the reliability of the equipment used in the mining industry. In doing so, a combined approach based on the reliability analysis, statistical inference and a machine learning technique is proposed. A case study was conducted on haul trucks in a mining operation. The case study showed that the reliability drops of haul trucks vary in the range of 0.84% and 2.45% in a shift. It was also calculated that 16.9% of these reliability drops were associated with operator habits. A truck's condition at the beginning of a shift and the initial reliability contribute to 36.3% and 31.1% of the reliability drops, respectively. The findings can be used in scheduling training programs, short-term mine planning, and simulation of material handling systems.

In the mineral industries, the heavy equipment is widely used, and the operator performance is a significant factor for fulfilling intended functions of this equipment. This study aims to analyse and interpret the effect of the human factor on the reliability of the equipment used in the mining industry. In doing so, a combined approach based on the reliability analysis, statistical inference and a machine learning technique is proposed. A case study was conducted on haul trucks in a mining operation. The case study showed that the reliability drops of haul trucks vary in the range of 0.84% and 2.45% in a shift. It was also calculated that 16.9% of these reliability drops were associated with operator habits. A truck's condition at the beginning of a shift and the initial reliability contribute to 36.3% and 31.1% of the reliability drops, respectively. The findings can be used in scheduling training programs, short-term mine planning, and simulation of material handling systems.

The operational efficiency of a mining enterprise is significantly determined by the operational reliability of its entire mining equipment. Insufficient operational reliability leads to production failures and, consequently, financial losses for the enterprise. A study of the root causes of production failures at several mining enterprises over more than twenty years has shown that the reliability of equipment at one stage of the process is significantly negatively impacted by the performance of equipment at other stages. Currently, this impact is not adequately considered by mining company managers and specialists when developing and implementing solutions aimed at improving the operational reliability of the entire mining equipment complex, limiting the potential for improving enterprise performance. This article substantiates the feasibility of developing and implementing a methodological approach for managers and specialists to improve the operational reliability of mining equipment based on the principle of "from the general to the specific." The approach under consideration differs from traditional ones in that the primary focus for improving the operational reliability of a mining equipment complex is not a single component or type of equipment, but the quality of the interconnections between equipment sets at various stages. Mastering this methodological approach allows the use of existing enterprise resources to prevent circumstances where a failure at one stage, even if not critical within that stage, triggers a cascade of failures at other stages, resulting in significant financial losses for the enterprise.

Appraising production targets through agent-based Petri net simulation of material handling systems in open pit mines

Mining equipment reliability: A review

This chapter presents various introductory aspects of mining equipment reliability, maintainability, and safety. The topics covered in the chapter are the need for improving mining equipment reliability, maintainability, and safety; mining equipment-related facts and figures, important terms and definitions, and useful information on mining equipment reliability, maintainability, and safety.