Abstract
This study presents a novel approach to optimizing energy consumption in rock destruction by integrating advanced design parameters of cutting elements. A hybrid experimental-computational model was developed to evaluate the specific energy of destruction () across granite, limestone, and sandstone. Key findings include energy savings of 15% in granite, 12.5% in limestone, and 13.7% in sandstone, achieved by optimizing the angle of attack – 30º, edge curvature – 0.5 mm, and applying wear-resistant DLC coatings 2500 HV. Laboratory tests, field experiments, and finite element simulations validated the model's accuracy within ±6%. The study identifies critical parameter interactions, such as angle of attack and coating hardness, reducing shear stresses and wear losses. These advancements lower operational costs by approximately $50,000 annually per excavator and extend tool life. Limitations include the limited range of rock types tested and slight simulation overestimations in abrasive sandstone. Future research should explore adaptive cutting element designs with real-time parameter adjustments using sensor-based systems and machine learning. The findings offer practical recommendations for implementing optimized tools in mining and construction, enhancing efficiency and cost-effectiveness. This work bridges theoretical insights and industrial applications, providing a scalable framework for energy-efficient rock destruction.