This paper attempts to apply the resilience concept to the mining sector, especially to mining machinery and productionsystems. The quantitative analysis method using the linear recovery function has been applied. As the core part of theproposed method, it is assumed that in the mining machinery fleet, the performance function falls to a “zero” value immediatelyafter the occurrence of a failure. Therefore, the resilience calculation process runs through the concept of timeto repair and machine maintainability. As a case study for the proposed concept, the operation and failure data of thedrum shearer machine in Parvadeh longwall mine in Iran is applied. The data pertains to a coal cutting operation in awhole longwall panel over the period of two years. In total, the calculations encompass over 2600 hours of actual operationand 171.8 hours of repair time, which reveals that the studied shearer has a resilience of 96.7 percent. Along with thecase study results, it is confirmed by this paper that resilience as a developing concept could be adequately applied to coalmining systems as a support measure for production assurance and reliability.

Maintenance is crucial to ensure production/output and customer satisfaction in the mining sector. The cost of maintenance of mechanised and automated mining systems is very high, necessitating efforts to enhance the effectiveness of maintenance systems and organisation. For effective maintenance planning, it is important to have a good understanding of the reliability and availability characteristics of the systems. Determining the Mean Residual Life (MRL) of systems allows organisations to more effectively plan maintenance tasks. In this paper, we use a statistical approach to estimate MRL and consider a Weibull proportional hazard model (PHM) with time-independent covariates to model the hazard function so that the operating environment could be integrated into the reliability analysis. The paper explains our methods for calculating the conditional reliability function and computing the MRL as a function of the current conditions. The model is verified and validated using data from the hydraulic system of LHD equipment in a Swedish mine. The results are useful to estimate the remaining useful life of such systems; the method can be used for maintenance planning, helping to control unplanned stoppages of highly mechanised and automated systems.

Although mining production depends on various equipments, significant amount of production loss can be attributed a specific equipment or fleet. Bottleneck is defined not only by production loss but also by our satisfaction from the equipment. The user satisfaction could be measured as machine effectiveness. Mining literature on performance improvement and optimization of equipment operations assert importance of availability, utilization and production performance as key parameters. These three parameters are useful for evaluating effectiveness of equipment. Mine production index (MPI), which can represent the effect of these factors, has been applied for continuous operation in mining. MPI uses Fuzzy Delphi Analytical Hierarchy Process to determine importance of each three parameter for individual equipment. A case study in a Swedish open pit mine was done to evaluate the field application of MPI. The results reveal that crusher is the bottleneck equipment in studied mine. As a methodical approach, an algorithm which uses MPI and detects bottleneck in continuous mining operation has been proposed.

Drilling rigs are widely used in mine development or construction and tunnel engineering projects. The rig consists of 12 subsystems in a series configuration and can be driven by diesel or electrical engines. This paper uses the Kamat-Riley (K-R) event-based Monte Carlo simulation method to perform reliability analysis of an underground mine drilling rig. For data analysis and to increase statistical accuracy, the paper discusses three case studies in an underground mine in Sweden. Researchers built a process to programme the simulation process and used MATLABTM software to run simulations. The results showed the simulation approach is applicable to the reliability analysis of this rig. Moreover, the reliability of all rigs reaches almost zero value after 50 h of operation. Finally, the differences between the reliability of the studied fleet of drilling rigs are a maximum 10 %. Therefore, all maintenance or spare part planning issues can be managed in a similar way

Switches and crossings (S&Cs) connect the rail network, guiding trains from one track to another and supporting path crossing. They are critical systems given the frequency of their functional failure and the consequences on the operation, cost and safety of railway transportation. Reliability studies are required to support the transport objective of providing dependable, sustainable and cost effective transportation. The main objective of this study is to assess the reliability characteristics of S&Cs based on field data collection. As field failure data have censored nature, commercial packages have not been satisfactory for processing them; therefore, the study uses a special statistical software package RDAT® (Reliability Data Analysis Tool). The availability of the studied switches and crossings is estimated based on the estimated reliability characteristics. The results show the availability of the S&Cs varies between x and y. This is useful information, as it helps the contractor plan and schedule maintenance. It also helps the asset owner to identify units whose performance is below the desired target and to make replacement decisions.

Rotary drilling machines are the most common machines used for drilling the blast holes in mining and constructions activities. The vital role of drilling operation in mining activities reveals that, the performance analysis of drilling machines and their failure and repair behaviors are essential. There-fore, the present study focuses on the reliability, availability and maintainability (RAM) of drilling ma-chines. In this paper, four rotary drilling machines at Sarcheshmeh Copper Mine in Iran are considered for repair and failure data collection. RAM analysis of drilling machines is done using Markov Approach. Results show that the reliability of drilling fleet is decreased by 0.67% in per hour drilling. The hydraulic system is the main unavailability reason of all machines. Moreover, the most failures of the two newest machines are completely repaired in 25 hours

Reliability centered maintenance (RCM) was initiated on 1960s in Boeing company to optimize the maintenance process of aircrafts. Since that date, this method has been applied in wide range of industries and has provided a completely positive results and recommendations for implementation in other industries. RCM is a systematic approach to quantitatively assess and optimize the performance of preventive maintenance tasks and to eliminate non-value adding maintenance actions. It provides considerable cost savings due to optimum maintenance effort, increased safety and productivity. This research considers the feasibility of applying the RCM methodology to fully-automated underground mining machineries as one of the vital requirement of early future modern mining. For this purpose, a literature review has been done to clarify the advantages, requirements, issues and challenges of RCM in other industries such as aviation, marine, nuclear, oil and gas, and process industries. It has been tried to analyze the RCM procedure in detailed and to have a look on the adoption issues and requirement for RCM implementation in fully-automated mining. Mainly, in this research, following RCM documents and standards were used for feasibility study: • Classic RCM in Aviation industry (SAE-JA1011, SAE-JA1012)• NASA RCM guidelines • USA’s military standards MIL-STD-2173• International Atomic Energy Agency (IAEA) RCM documentUsing the above mentioned documents, an implementation issues and challenges in developing a RCM program for fully-automated underground mining machineries has been presented. The result of this study shows that RCM is applicable in maintenance planning for fully-automated underground mining machinery. Because, serious safety restrictions are associated with this kind of mining operation and RCM can properly help the engineers to analyze the safety consequences of any failure and make the best decision for maintenance tasks. However, practical application of RCM has some differences in mining context which in this project are discussed in detail. The investigations show the risk priority number is the suitable measure to select the RCM target component/system. Since, there is no operation in site, detective the some evident failures are become impossible in automated mining. Therefore, we have to consider the smartness level and capabilities of agent-based supervisors to get the real feeling of machinery health and operation condition. Internet of Thing platforms are also required in fully automated mine to develop the machine-to-machine communication and to reduce the risk of failures and failure propagation in fleet level. RCM could apply the outcomes of these advanced technologies to optimize the maintenance actions in automated mines.