M. Mohseni; M. Ataei
Abstract
In this work, the time series modeling was used to predict the Tazareh coal mine risks. For this purpose, initially, a monthly analysis of the risk constituents including frequency index and incidence severity index was performed. Next, a monthly time series diagram related to each one of these indices ...
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In this work, the time series modeling was used to predict the Tazareh coal mine risks. For this purpose, initially, a monthly analysis of the risk constituents including frequency index and incidence severity index was performed. Next, a monthly time series diagram related to each one of these indices was for a nine year period of time from 2005 to 2013. After extrusion of the trend, seasonality, and remainder constituents of the time series modeling, the final time series model of the indices was determined with high precision. The precision level of the resulting model was evaluated using the root mean square error (RMSE) method. The values obtained for the severity index and accident frequency index were 0.001 and 6.400, respectively. Evaluation of the seasonal time series constituent of the frequency index showed that, yearly, most number of accidents occurred in April, and the least one took place in January. Additionally, evaluation of the seasonal time series constituent of the severity index showed that, every year, the severest accidents occurred in October, and the least ones happened in January. Using the final model, a monthly prediction of indices was performed for a four year period of time from 2014 to 2017. Subsequently, using the known mean work hours in the mine, predictions of the number of accidents and the number of work days lost within a similar time period were made. The prediction results showed that in the future, the number of accidents and the number of work days lost would have a down-going trend such that for similar months, annually, an average 22% decrease in the number of accidents and an average 24% decrease in the number of work days lost are expected.
R. Mikaeil; M. Abdollahi Kamran; G. Sadegheslam; M. Ataei
Abstract
Predicting the sawability of the dimension stone is one of the most important factors involved in production planning. Moreover, this factor can be used as an important criterion in the cost estimation and planning of the stone plants. The main purpose for carrying out this work was to rank the sawability ...
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Predicting the sawability of the dimension stone is one of the most important factors involved in production planning. Moreover, this factor can be used as an important criterion in the cost estimation and planning of the stone plants. The main purpose for carrying out this work was to rank the sawability of the dimension stone using the PROMETHEE method. In this research work, four important physical and mechanical properties of rocks including the uniaxial compressive strength, Schmiazek F-abrasivity, mohs hardness, and Young's modulus were evaluated as the criteria. During the research process, two groups of dimension stones were selected and analyzed. The rock samples were collected from a number of Iranian factories for the laboratory tests. The production rate of each sawn stone was selected to verify the proposed sawability ranking method. The results obtained showed that the new ranking method can be reliably used for evaluating the sawability of the dimension stone at any stone factory with different rocks only by the physical and mechanical properties testing.
S. Mohammadi; M. Ataei; R. Khalokakaei; E. Pourzamani
Abstract
Optimization of the exploitation operation is one of the most important issues facing the mining engineers. Since several technical and economic parameters depend on the cut-off grade, optimization of this parameter is of particular importance. The aim of this optimization is to maximize the net present ...
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Optimization of the exploitation operation is one of the most important issues facing the mining engineers. Since several technical and economic parameters depend on the cut-off grade, optimization of this parameter is of particular importance. The aim of this optimization is to maximize the net present value (NPV). Since the objective function of this problem is non-linear, three methods can be used to solve it: analytical, numerical, and meta-heuristic. In this study, the Golden Section Search (GSS) method and the Imperialist Competitive Algorithm (ICA) are used to optimize the cut-off grade in mine No. 1 of the Golgohar iron mine. Then the results obtained are compared. Consecuently, the optimum cut-off grades using both methods are calculated between 40.5% to 47.5%. The NPVs obtained using the GSS method and ICA were 18487 and 18142 billion Rials, respectively. Thus the value for GSS was higher. The annual number of iterations in the GSS method was equal to 18, and that for ICA was less than 18. Also computing and programming the process of golden section search method were easier than those for ICA. Therefore, the GSS method studied in this work is of a higher priority.
M. M Tahernejad; M. Ataei; R Khalokakaie
Abstract
Iran has high potential and unique stone reserves in terms of variety of color, texture, quality, and economic value; nevertheless, in spite of growing mine production during the past decade, in many instances this potential has been overlooked. Therefore it is necessary to investigate strategic factors ...
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Iran has high potential and unique stone reserves in terms of variety of color, texture, quality, and economic value; nevertheless, in spite of growing mine production during the past decade, in many instances this potential has been overlooked. Therefore it is necessary to investigate strategic factors of these mines. The purpose of this study is to evaluate and determine the best strategies for Iran’s quarries. To this end, the mines were analyzed using the Strengths, Weaknesses, Opportunities and Threats (SWOT) approach in combination with Fuzzy Analytic Hierarchy Process (FAHP). Firstly, an environmental analysis was performed and then the SWOT factors were identified. In this way, the sub-factors which have very significant effects on the mines were determined. Using the SWOT matrix, alternative strategies were developed. Subsequently, the strategies were prioritized and the best strategies for these mines were determined. The results show that conservative strategies are the best strategy group for Iran’s quarries.
