Efficient Cable Shovel Excavation in Surface Mines

Abstract

The cable shovel is widely used in surface mining. High operating and ownership costs necessitate efficient use of the cable shovel. Operator practices have long been suspected to contribute towards the inefficient use of the shovel. Crowd arm and hoist rope speeds are key measures of operator practices. The objective of this work is to find the crowd arm and hoist rope speeds for optimal shovel performance for given initial conditions and material properties. Shovel kinematics and dynamic modeling, using shovel geometry and the simultaneous constraint method, respectively, have been employed to build models of the excavation process. Dynamic models of the shovel payload and the material cutting resistance have also been developed using geometric simulation and passive soil pressures techniques, respectively. These models are solved numerically by combining Runge–Kutta and Gaussian elimination algorithms to compute the work done and the resistive forces during shovel excavation. The algorithms have been combined into a shovel simulator. The simulator has been used to simulate the P&H 2100BL shovel. The simulation results indicate that input energy and digging time increase with increasing crowd arm and decreasing hoist rope speeds. The input energy per unit loading rate is proposed as an appropriate measure of shovel performance. High energy per unit loading rate occurs for high crowd speeds and low hoist rope speeds. For the simulated conditions and crowd arm and hoist rope speeds ranging from 0.25 to 0.5 ms−1 and 0.5 to 0.7 ms−1, respectively, the optimal crowd arm and hoist rope speeds were found to be 0.25 ms−1 and 0.7 ms−1, respectively, and the objective function value was 0.21 KJs/kg. This work establishes, theoretically, the fact that operator practices have an effect on shovel performance and is useful in establishing optimum practices. The results are the initial steps towards full automation of the excavation process.