Waste Dump Site Selection by Using Fuzzy VIKOR

Considering the nature of open pit mines, harvest volume, it usually is required to remove a lot of waste to access to mineral planned grade. So, one of the most important part of open pit mines design, is waste dump site selection. Many factors are effective in waste dump site selection. These factors are sometimes in conflict with each other. So selecting the desired location for waste dump is a process complex and multi-criteria decision making. There are a variety of methods for decision making under complicated condition, such as fuzzy, Delphi, multi-criteria decision making and Expert system methods can be hinted. VIKOR method, which is one of the decision making multi criteria methods, is useful tool for decision-making. On the other hand with regard to uncertainty in decision-making, fuzzy approach is a useful tool for this purpose. This article has tried to select the best waste dump site in Sari Gunay Gold Mine by Fuzzy VIKOR. The results show that C position has a higher priority than other positions

Forecasting the Number of Fatal Injuries in Underground Coal Mines

Most management decisions at all levels of the organization are as directly or indirectly depends on the circumstance of future. With regard to predict the future events in the process of decision-making plays a main role, therefore, forecasting is very important for every organizations and institutions. There is a variety of methods to predict time series. In general, these techniques can be divided as following: statistical, artificial intelligence and analytical techniques. Two of the most common methods for time series prediction is autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) methods, these methods are the subset of statistical and artificial intelligence techniques respectively. In this paper, a hybrid model of ARIMA and ANN models are employed to predict the number of fatal injuries in the USA underground coal mines. This research showed the result of hybrid model is better than split model

Evaluating Underground Mining Hazards by Fuzzy FMEA

Managers always look for systems with minimum hazards. The hazards create problems for performance of projects. The largest and most important hazards of working underground mine can be related to health, safety and environmental, because if one of these sectors be in hazard, maybe lead to close mine. Failure mode and effects analysis (FMEA) is a widely used quality improvement tool to identify the potential failure modes for measuring reliability of a product or a process. FMEA is performed by developing a risk priority number (RPN), which is the product of severity, occurrence, and detection ratings. On the other hand,with regard to uncertainty in the decision-making, fuzzy theory will be able to model this uncertainty. Fuzzy FMEA provides a tool that can work in a better way with vague concepts and without sufficient information than conventional FMEA. This article by using Fuzzy FMEA and based on HSE criteria evaluate hazards of Parvade No. 1 Mine in Tabas Coal Mine. The results demonstrate the most hazardous parameter is rock burst in this mine

Risk Assessment in Block Cave Mining

Mining Ventures are considered as high risk projects and therefore managing the risks is inevitable. Risk assessment is an important part of the complex process of risk management, hence applying appropriated and practical methods for ranking the risks associated with projects, can help to perform a better risk management. In this research the applicability of using Techniques for Order Preference by Similarity to Ideal Solution (TOPSIS) method for risk ranking in an underground mine, extracting by block caving method, was studied. Via this method, the risk associated with reserve estimation ranked as the first while in conventional method (P-I Matrix method) located in the sixteenth. Also there were significant differences in ranks of the other risks. Considering the more criteria, with different weights, in comparison with conventional methods, the results comprised from TOPSIS method are more reliable. By implementing this method risks are ranked better and more realistic and consequently then will be managed more efficient