Digital Modeling of Quarry Transport to Reduce Fuel and Environmental Costs

The article presents a digital model for selecting the optimal transport type for hauling dimension stone blocks in quarry operations. The model integrates fuel consumption, transportation cost, block geometry, and pollutant emissions, providing a combined techno-economic and environmental assessment of transportation scenarios. Developed in Google Colab with Python, it ensures flexibility and is linked to Google Sheets for real-time data input without additional software. Key parameters include transport type, road gradient, traction coefficients, equipment productivity, seasonality, fuel use, and emissions of CO₂, NOₓ, SO₂, and PM.The model was tested on production data from the Southern section of the Mezhyrichchia quarry using a CAT 980H wheel loader and a KrAZ-65055 dump truck. Results show that optimized transportation scenarios can cut fuel consumption by up to 31% and reduce costs per 1 m³ by 26%. At the same time, emissions per 1 m³ of commercial stone blocks can be lowered by up to 30% through appropriate equipment selection and reduced idle trips. The model can serve as a decision-support tool in real-time quarry operations, helping minimize fuel overuse and ecological risks. Adapted for small-scale enterprises, it can also be implemented as a mobile application.