This paper aims to develop a computer simulation processing method to simulate the mining operation of self-advancing semi-continuous mining technology and optimize the shift step of belt conveyor by using simulation modeling framework based on intelligent objects (SIMIO). The method would effectively solve the challenge of field testing such large-scale equipment.
The four operational modes of self-advancing semi-continuous mining technology at single bench had been illustrated. The operational system of this technology was analyzed and broken down to single units. By analyzing the time constitution of one operation cycle, the theoretical optimization model of shift step can be established and the optimization criteria is the time utilization ratio being maximum. Once the simulation flow was determined, a three-dimensional (3D) computer simulation model of this mining technology was developed by adapting the SIMIO simulating software to the theoretical model. The models were run to investigate the outputs from different operational modes using geological and mining data from East open-pit mine.
The result of these simulations showed that the four-mining-width one-shift (FMWOS) is at maximum production capacity during all operation modes. If transfer equipment is necessary, then this mode can adapt, but system will become more complex. There are minor differences between two-mining-width one-shift and three-mining-width one-shift. If transfer equipment is not necessary, then the two-mining-width one-shift can adapt during actual production.
The simulation results show that the proposed method can achieve the optimal shift step of a belt conveyor and effectively reduce the time loss caused by the coordination of multiple pieces of equipment while simultaneously improving operational efficiency.
This work was supported by Natural Science Foundation of Hebei Province.
Li, X., Li, L., Lv, H. and Guan, T. (2017), "The shift step optimization of belt conveyor in self-advancing semi-continuous mining technology based on SIMIO", World Journal of Engineering, Vol. 14 No. 4, pp. 324-328. https://doi.org/10.1108/WJE-10-2016-0116
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