Abstract

Evaluating the reserves of commercial blocks in dimension stone quarries requires determining in situ block geometry. Furthermore, to extract blocks, the planes need to be cut, and the intersection between the fracture network and the cutting patterns forms smaller blocks. The optimization of the cutting patterns can increase quarrying efficiency, resulting in less environmental damage. In this paper, a numerical algorithm was selected from various algorithms and was developed for in situ block identification. The optimization approach was adopted to increase quarry productivity and to investigate quarrying direction on a large scale. However, on a small scale, this approach was employed for checking the distance between the cutting planes. According to the algorithms developed, 3D-QuarryOptimizer was programmed in the MATLAB environment to determine the geometry of the blocks and to optimize extraction based on the quality classification of the blocks formed. The algorithms developed have such advantages as the optimization approach and taking the geometry of the blocks into consideration. This methodology was applied in a marble quarry and a granite quarry. Research conducted in the granite quarry showed that the program is a practical tool to determine the geometry of in situ blocks and their quality classification. The marble quarry was studied for the optimization phase. The large-scale optimization indicated a maximum difference of 17% in the yield among several quarrying directions. On a small scale, however, a 120% increase in quarry yield was achieved with the optimal interval between the cutting planes.

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