MJERENJE OTPORNOSTI STROJEVA ZA ŠIROKOČELNO ISKAPANJE

This paper attempts to apply the resilience concept to the mining sector, especially to mining machinery and production systems. The quantitative analysis method using the linear recovery function has been applied. As the core part of the proposed method, it is assumed that in the mining machinery fleet, the performance function falls to a “zero” value immediately after the occurrence of a failure. Therefore, the resilience calculation process runs through the concept of time to repair and machine maintainability. As a case study for the proposed concept, the operation and failure data of the drum shearer machine in Parvadeh longwall mine in Iran is applied. The data pertains to a coal cutting operation in a whole longwall panel over the period of two years. In total, the calculations encompass over 2600 hours of actual operation and 171.8 hours of repair time, which reveals that the studied shearer has a resilience of 96.7 percent. Along with the case study results, it is confirmed by this paper that resilience as a developing concept could be adequately applied to coal mining systems as a support measure for production assurance and reliability.U radu je opisana primjena koncepta otpornosti u rudarstvu, tj. u radu strojeva koji se rabe kod iskapanja i proizvodnje. Uporabljena je linearna funkcija kao kvantitativna analitička metoda. Pretpostavljeno je kako performanse rudarske opreme padaju na nulu odmah nakon događaja koji označava kvar. Slijedom toga izračun otpornosti postupak je koji u obzir uzima vrijeme potrebno za popravak strojeva u prvobitno radno stanje. Studija slučaja načinjena je s podatcima o kvarovima utvrđenim na sjekačima korištenim u iranskome rudniku (s uzdužnim iskapanjem) Parvadeh i obuhvaćaju dvogodišnje razdoblje vađenja ugljena. Kroz to vrijeme obrađeni su podatci za više od 2600 radnih sati te 171,8 sati utrošenih na popravke. Obradom je izračunano kako otpornost promatranih sjekača iznosi 96,7 %. Potvrđeno je kako takva otpornost može biti primijenjena kod rudarenja ugljena kao dodatna varijabla kojom se opisuje stabilnost i pouzdanost vađenja rude

Artificial neural network to predict the health risk caused by whole body vibration of mining trucks

Drivers of mining trucks are exposed to whole-body vibrations (WBV) and shocks during the various working cycles. These exposures have an adversely influence on the health, comfort and also working efficiency of drivers. Determination and prediction of the vibrational health risk of the mining haul trucks at thevarious operational conditions is the main goal of this study. To this aim, three haul roads with low, medium and poor qualities are considered based on the ISO 8608 standard. Accordingly, the vibration of a mining truck in different speeds, weights and distribution qualities of the materials in the dump body are evaluated for each haul road quality using the Trucksim software. An artificial neural network (ANN) is used to predict the vibrational health risk. The obtained results indicate that the haul road qualities, the truck speeds and the accumulation sides of material in the truck dump body have significant effects on the root mean square (RMS) of vertical vibrations. However, there is no significant relation between the material’s weight and the RMS values. Also, the application of ANN revealed that there is a good correlation between the predicted and simulated RMS values. The performance of the proposed neural network to predict the moderate and high health risk are 88.11% and 93.93% respectively</span

Reliability and operating environment based spare parts planning

The required spare parts planning for a system/machine is an integral part of the product support strategy. The number of required spare parts can be effectively estimated on the basis of the product reliability characteristics. The reliability characteristics of an existing machine/system are influenced not only by the operating time, but also by factors such as the environmental parameters (e.g. dust, humidity, temperature, moisture, etc.), which can degrade or improve the reliability. In the product life cycle, for determining the accurate spare parts needs and for minimizing the machine life cycle cost, consideration of these factors is useful. Identification of the effects of operating environment factors (as covariates) on the reliability may facilitate more accurate prediction and calculation of the required spare parts for a system under given operating conditions. The Proportional Hazard Model (PHM) method is used for estimation of the hazard (failure) rate of components under the effect of covariates. The existing method for calculating the number of spare parts on the basis of the reliability characteristics, without consideration of covariates, is modified and improved to arrive at the optimum spare parts requirement. In this research an approach has been developed to forecast and estimate accurately the spare parts requirements considering operating environment and to create rational part ordering strategies. Subsequently, two models (exponential and Weibull reliability based) considering environmental factors are developed to forecast and estimate the required number of spare parts within a specific period of the product life cycle. This study only discusses non-repairable components (changeable/service parts), which must be replaced upon failure. To test the models, the data collection and classification was carried out from two mining company in Iran and Sweden and then the case studies concerning spare parts planning based on the reliability characteristics of parts, with/without considering the operating environment were done. The results show clearly the differences between the consumption patterns for spare parts with and without taking into account the effects of covariates (operating environment) in the estimation. The final discussion treats a risk analysis of not considering the system’s working conditions through a non-standard (new) event tree approach in which the organizational states and decisions were included and taken into consideration in the risk analysis. In other words, we used the undesired states instead of barriers in combination with events and consequent changes as a safety function in event tree analysis. The results of this analysis confirm the conclusion of this research that the system’s operating environment should be considered when estimating the required spare parts.Godkänd; 2005; 20061001 (ysko

Product support and spare parts considering system reliability and operating environment

The required spare parts planning for a system/machine is an integral part of the product support strategy. The number of required spare parts can be effectively estimated on the basis of the product reliability characteristics. The reliability characteristics of an existing machine/system are influenced not only by the operating time, but also by factors such as the environmental parameters (e.g. dust, humidity, temperature, moisture, etc.), which can degrade or improve the reliability. In the product life cycle, for determining the accurate spare parts needs and for minimizing the machine life cycle cost, consideration of these factors is useful. Identification of the effects of operating environment factors (as covariates) on the reliability may help in the prediction and calculation of the required spare parts for a system under given operating conditions, which constitutes the research problem studied in this thesis. The Proportional Hazard Model (PHM) method is used for estimation of the hazard (failure) rate of components under the effect of covariates. In this research an approach has been developed to forecast and estimate accurately the spare parts requirements and to create rational part ordering strategies. Subsequently, a model considering environmental factors is developed to forecast and estimate the required number of spare parts within a specific period of the product life cycle. This thesis only discusses non- repairable components (changeable/service parts), which must be replaced after failure. In addition, the existing method for calculating the number of spare parts on the basis of the reliability characteristics, without consideration of covariates, is modified to arrive at the optimum spare parts requirement. To test the model, case studies concerning spare parts planning based on the reliability characteristics of parts and with/without considering the operating environment have been carried out. The results show clearly the differences between the consumption patterns for spare parts with and without taking into account the effects of covariates in the estimation. The final discussion treats spare parts logistics and inventory management. In this work an attempt is made to minimize the inventory cost and consequently the product life cycle cost. Two models for ordering, purchasing and storing spare parts are discussed in connection with the inventory management.Godkänd; 2003; 20070215 (ysko

Product support and spare parts considering system reliability and operating environment

The required spare parts planning for a system/machine is an integral part of the product support strategy. The number of required spare parts can be effectively estimated on the basis of the product reliability characteristics. The reliability characteristics of an existing machine/system are influenced not only by the operating time, but also by factors such as the environmental parameters (e.g. dust, humidity, temperature, moisture, etc.), which can degrade or improve the reliability. In the product life cycle, for determining the accurate spare parts needs and for minimizing the machine life cycle cost, consideration of these factors is useful. Identification of the effects of operating environment factors (as covariates) on the reliability may help in the prediction and calculation of the required spare parts for a system under given operating conditions, which constitutes the research problem studied in this thesis. The Proportional Hazard Model (PHM) method is used for estimation of the hazard (failure) rate of components under the effect of covariates. In this research an approach has been developed to forecast and estimate accurately the spare parts requirements and to create rational part ordering strategies. Subsequently, a model considering environmental factors is developed to forecast and estimate the required number of spare parts within a specific period of the product life cycle. This thesis only discusses non- repairable components (changeable/service parts), which must be replaced after failure. In addition, the existing method for calculating the number of spare parts on the basis of the reliability characteristics, without consideration of covariates, is modified to arrive at the optimum spare parts requirement. To test the model, case studies concerning spare parts planning based on the reliability characteristics of parts and with/without considering the operating environment have been carried out. The results show clearly the differences between the consumption patterns for spare parts with and without taking into account the effects of covariates in the estimation. The final discussion treats spare parts logistics and inventory management. In this work an attempt is made to minimize the inventory cost and consequently the product life cycle cost. Two models for ordering, purchasing and storing spare parts are discussed in connection with the inventory management.Godkänd; 2003; 20070215 (ysko

Maintenance spares inventory management : performance measurement using a HOMM

Spare parts inventory management differs from both work-in-process inventory management and finished product inventory management mainly due to its unique aspects in function with maintenance. Furthermore, its inventory management shows more complexities and the performance measurement differs from other productions’ either. Studies both in theoretical research and in practice have shown that only some concrete figures had been considered in traditional KPI’s for spare parts inventory management, including the total stock value, cost of keeping stock, critical spares stock-outs, operational downtime due to stock-outs, rate of circulation, etc. However, such KPI’s may only reflect limited results from spares inventory management. In another word, they can not help to find out the root causes of which aspects are the management’s bottlenecks, or from which aspects it can be improved step-by-step. This paper aims to propose a new way to measure the performance of spares inventory management from the perspective of a House of Maintenance Management (HOMM). First, the HOMM-Spares with PDSA (Plan, Do, Study, Act) thinking will be promoted with the consideration of spares management. Second, management review for spares inventory using the HOMM-Spares will be discussed in details and the performance measurement will be clarified. Obviously, with the new promoted measurement system, we can not only review its performance from a more systematic standing point, but also, the continuously improvement plan with a more scientific analysis will be achieved simultaneously. How to support decision making with this spares performance measurement system is demonstrated as well with a case study.Godkänd; 2011; 20120110 (ysko

Reliability analysis of the compressed air supplying system in underground mines

Despite the high cost and low efficiency, compressed air is mostly used in underground mining for ore extraction, hoisting, and mineral processing operations. Failures of compressed air systems not only threaten the health and safety of workers but also contribute to inefficient control of airflow and stopped all equipment that operates by compressed air. In such uncertain conditions, mine managers are faced with the big challenge to supply enough compressed air, and therefore, the reliability evaluation of these systems is essential. This paper aims to analyze the reliability of the compressed air system using the Markov modeling approach as a case study, Qaleh-Zari Copper Mine, Iran. To achieve this, the state space diagram was constructed considering all relevant states for all compressors in the main compressor house of the mine. The failure and repair rate of all main and reserve compressors were calculated for all possible transitions between states to obtain the probability of being of the system in each of the states. Moreover, the probability of failure at any time period was considered to study the reliability behavior. The results of this study show that there is 31.5% probability that the compressed air supplying system is in operating condition with two main and one standby compressors. The system probability that two main compressors are remain in the operation without failure for one months is 92.32%. Furthermore, the lifetime of the system is estimated 33 months when at least one main compressor is active.Validerad;2023;Nivå 2;2023-05-10 (hanlid)</p

Reliability Analysis of Switches and Crossings : A Case Study in Swedish Railway

It is reported that switches and crossings (S&amp;C) are one of the subsystems that cause the most delays on Swedish Railways while accounting for at least 13% of maintenance costs [6]. It is the main reason why we chose to base our study on this subsystem. Intelligent data processing allows understanding the real reliability characteristics of the assets to be maintained. The first objective of this research is to determine the S&amp;C reliability characteristics based on field data collection. Because field failure data are typically strongly censored, an especial statistics software package was developed to process field failure data, as commercial packages have not been found satisfactory in that respect. The resulting software, named RDAT® (Reliability Data Analysis Tool) has been relied upon for this study: it is especially adapted to statistical failure data analysis. In the next step the availability of studied switches and crossings is estimated based on the reliability characteristics founded in the first step

Assessment of Reliability-Related Measures for Drum Shearer Machine : a Case Study

Longwall mining is one of the most continuous and productive mining methods. Efficiency of this method is directly affected by the involved machineries and systems. The drum shearer plays an important role in the face productivity and the mine life. Therefore, monitoring of this machine can lead the whole extraction operation to a high level of production and safety. There are several reliability-related measures for evaluation of the mining equipment. Availability, utilization, production efficiency and overall production effectiveness are the most important measure which can help us in this way. In this paper, the production and failure data of a drum shearer machine in Parvade coal mine in Iran have been collected from whole of one longwall panel during a two-year period. The mentioned reliability-related measures have been calculated based on the total uptime and downtime of the machine. The results showed that, the studied drum shearer is in good availability level. However, it has average production efficiency, very low utilization and very low overall equipment effectiveness. Also, high waiting and idling time raises from other machineries during the extraction process, was recognized as the main reason for the current low productivity of shearer machine in mine.Godkänd; 2014; 20140817 (hadhos)CAMM - Lean minin