Abstract- Blast fragmentation significantly influences the efficiency of loading equipment such as shovels in surface coal mines. Proper fragmentation ensures ease of digging, shorter cycle times, lower fuel usage, and reduced wear and tear on machinery, ultimately enhancing overall mine productivity. This review paper systematically analyzes past research focused on the relationship between blast design parameters—such as burden, spacing, explosive type, and powder factor—and the resulting rock fragmentation. It further explores how these factors impact shovel performance in terms of loading rate, bucket fill factor, and operational costs. Several case studies and field experiments were reviewed to identify effective practices in controlled blasting aimed at optimizing shovel efficiency. The review underscores key challenges, including the lack of integrated models that link blast design directly to shovel productivity, inconsistencies in fragmentation results across different mine sites, and the underutilization of modern tools like digital image analysis and artificial intelligence for predictive modeling. These research gaps hinder the full optimization of the blast-to-load cycle. The paper concludes by recommending a more integrated and technology-driven approach to blast planning, encouraging the use of real-time monitoring, data analytics, and adaptive blast models to enhance shovel performance and improve the economic efficiency of surface mining operations. Keywords: Blast fragmentation, shovel efficiency, surface coal mine, powder factor, rock size distribution, productivity, digital image analysis, mine-to-mill.
Raidas et al. (2026) studied this question.