Mathematical model for fleet sizing using the match factor in an open-pit mine

Abstract

The open-pit mining industry is vital to the global economy, facing challenges in operational efficiency and cost management. Fleet sizing is crucial for optimization, requiring innovative approaches. Discrete event simulation using Arena software addresses fleet sizing complexities in open-pit mines, aiding in understanding operational delays and high costs. This research aims to develop a framework integrating process modeling and simulation in Arena, enabling real-time fleet decisions. The study reviews mining process simulation literature, open-pit mine characteristics, and proposes detailed models for geology, topography, and mining operations. Critical variables like equipment performance, productivity, and truck hours will be evaluated. Results aim to provide mining companies a valuable decision-making tool for efficient resource management and cost reduction. The study also explores simulation-based decision-making implications for sustainability and environmental responsibility in mining. Overall, this research contributes to open-pit mining optimization, utilizing Arena software for innovative fleet sizing decisions.