Optimum Equipment Allocation Under Discrete Event Simulation for an Efficient Quarry Mining Process

Abstract

This study presents a discrete event simulation model to minimize operating costs in quarry mining processes by determining the optimal allocation of backhoes and dump trucks, which are the primary mining equipment. The modeling focuses on four principal vehicle types (24-ton dump truck, 2.0 m3 backhoe, 41-ton dump truck, 4.64 m3 backhoe) commonly deployed in quarry mining. The simulation replicates the sequential mining stages involving soil removal, rock ripping (weathered rock or weathered soil), and blasting operations. This methodology is applied to a case study of mining process planning under resource constraints, incorporating real-world quarry conditions in South Korea. Results demonstrate that optimizing the number of equipment units reduces construction costs and shortens the construction period by decreasing dump truck waiting times. When the number of backhoes is limited to 10 during operations, findings indicate an increase in costs and a gradual decline in net profit. Additionally, the interaction between the 24-ton and 41-ton dump trucks is shown to influence the optimal allocation strategy. The simulation-based optimization executes iterative experiments for each scenario, yielding statistically robust results within a 95% confidence interval, thereby supporting informed decision-making for managers.