Effects of microfabric on drillability of rocks

Bulletin of Engineering Geology and the Environment - Quantifying the rock microfabric is one of the most important research interests and challenges in the field of rock drilling and excavation....     

Context-driven mean residual life estimation of mining machinery

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.     

Reliability-based maintenance scheduling of hydraulic system of rotary drilling machines

Hydraulic system has a critical and important role in drilling machines. Any failure in this system leads to problems in power system and machine operation. Since the failure cannot be prevented entirely, it is important to minimize its probability. Reliability is one of the most efficient and important method to study safe operation probability of hydraulic systems. In this research, the reliability of hydraulic system of four rotary drilling machines in Sarcheshmeh Copper Mine in Iran has been analyzed. The data analysis shows that the time between failures (TBF) of Machines A and C obey the Weibull (2P) and Weibull (3P) distribution, respectively. Also, the TBF of Machines B and D obey the lognormal distribution. With regard to reliability plots of hydraulic systems, preventive reliability-based maintenance time intervals for 80% reliability levels for machines in this system are 10 h.     

Reliability and maintainability analysis of electrical system of drum shearers

The reliability and maintainability of electrical system of drum shearer at Parvade.1 Coal Mine in central Iran was analyzed. The maintenance and failure data were collected during 19 months of shearer operation. According to trend and serial correlation tests, the data were independent and identically distributed (iid) and therefore the statistical techniques were used for modeling. The data analysis show that the time between failures (TBF) and time to repair (TTR) data obey the lognormal and Weibull 3 parameters distribution respectively. Reliability-based preventive maintenance time intervals for electrical system of the drum shearer were calculated with regard to reliability plot. The reliability-based maintenance intervals for 90%, 80%, 70% and 50% reliability level are respectively 9.91, 17.96, 27.56 and 56.1 h. Also the calculations show that time to repair (TTR) of this system varies in range 0.17∼4 h with 1.002 h as mean time to repair (MTTR). There is a 80% chance that the electrical system of shearer of Parvade.1 mine repair will be accomplished within 1.45 h.     

A new classification system for evaluating rock penetrability

This paper presents a new classification system called the Rock Penetrability index (RPi). An evaluation model based on the fuzzy Delphi analytic hierarchy process (FDAHP) has been used for estimation of penetrability and drillability of rocks. For this purpose, five parameters of the rock material, including uniaxial compressive strength, Schimazek's F-abrasivity, mean Moh's hardness, texture and grain size and Young's modulus have been investigated and rated. In the RPi system, a number from 10.25 to 100 can be assigned to each rock, with higher values corresponding to greater ease of drilling and penetration into rock. Based on the RPi classification, rocks are classified into five modes from the view point of penetrability: very poor, poor, medium, good and very good.     

Reliability modeling of hydraulic system of drum shearer machine

The hydraulic system plays an important role in supplying power and its transition to other working parts of a coal shearer machine. In this paper, the reliability of the hydraulic system of a drum shearer was analyzed. A case study was done in the Tabas Coal Mine in Iran for failure data collection. The results of the statistical analysis show that the time between failures (TBF) data of this system followed the 3-parameters Weibull distribution. There is about a 54% chance that the hydraulic system of the drum shearer will not fail for the first 50 h of operation. The developed model shows that the reliability of the hydraulic system reduces to a zero value after approximately 1 650 hours of operation. The failure rate of this system decreases when time increases. Therefore, corrective maintenance (run-to-failure) was selected as the best maintenance strategy for it.     

Development of a new classification system for assessing of rock mass drillability index (RDi)

The drilling process and its results are affected by various parameters of the rock material and rock mass. The effects of rock material have been emphasized in various studies; however lack of perfect knowledge of rock mass structural parameters may lead to unpredictable results. This paper presents a new classification system for specifying the rock mass drillability index (RDi). For this purpose, six parameters of the rock mass, including texture and grain size, Mohs hardness, uniaxial compressive strength (UCS), joint spacing, joint filling (aperture) and joint dipping have been investigated by physical modeling and rated. Physical modeling in particular has been used for investigating the effects of joint characteristics on drilling rate. In the proposed RDi system, each rock mass is assigned a rating from 7 to 100, with a higher rating corresponding greater ease of drilling. Based on the RDi rating, the drilling rate may be classified into five modes: slow, slow-medium, medium, medium-fast, and fast.     

Laboratorial studies for the prediction of rock texture and hardness using vibration measurement while drilling

Bulletin of Engineering Geology and the Environment - Rock hardness and texture are two dominant factors controlling such engineering characteristics of rocks as drillability, blastability, and...     

Modified Kuz—Ram fragmentation model and its use at the Sungun Copper Mine

Rock fragmentation, which is the fragment size distribution of blasted rock, is one of the most important indices for estimating the effectiveness of blast work. In this paper a new form of the Kuz—Ram model is proposed in which a prefactor of 0.073 is included in the formula for prediction of X_50. This new equation has a correlation coefficient that is greater than 0.98. In addition, a new approach is proposed to calculate the Uniformity Index, n. A Blastability Index (BI) is used to correct the calculation of the Uniformity Index of Cunningham, where BI reflects the uniformity of the distribution. Interestingly, this correction also can be observed in the Kuznetsov—Cunningham—Ouchterlony (KCO) model, which uses In situ block size as a parameter for calculating the curve-undulation in the Swebrec function. However, it is in contrast to prediction of X₅₀ as the central parameter in Swebrec and Rosin–Rammler distribution functions. The new model is a two parameter fragmentation size distribution that can be easily determined in the field. However, it does not consider the timing effect, or upper limit for sizes, as does the original Kuz—Ram model. The model is used at the Sungun Mine, and it does a good job of predicting the fines produced during blasting.