Study of Blast Fragmentation and Shovel Efficiency in a Surface Coal Mine

Abstract

A significant proportion of mineral production is derived from surface mining operations, which have witnessed rapid growth due to the deployment of high-capacity equipment. The need to meet rising demand for minerals has led to the extensive use of heavy earth moving machinery (HEMM) such as shovels, excavators, and dumpers. These machines represent substantial capital investments, and their performance must be optimized for cost-effective mining. Among the many factors influencing equipment efficiency, the results of blasting—particularly the fragmentation size, distribution, and muck pile profile—play a critical role in determining the productivity of excavation and loading operations. Therefore, proper blast design is fundamental to the economic success of surface mining projects. Traditional methods such as trial-and-error and cratering are no longer viable for large-scale operations due to inefficiency and unpredictability. While empirical methods remain widely used for estimating blast design parameters, advancements in computer modeling offer promising alternatives that combine precision and adaptability. The integration of empirical formulas, simulation-based approaches, and instrumented field trials can significantly improve fragmentation outcomes. However, computational techniques are still underutilized in routine mine planning. This dissertation focuses on identifying both controllable and uncontrollable parameters that affect surface blast design. Using the well-known model by Langefors and Kihlstrom (1978) as a foundation, a computer model was developed—first in C++ and later migrated to a Java-based platform using NetBeans IDE 6.5. The software incorporates a database and user-friendly interface to aid in predicting fragmentation and optimizing blast design. The model was tested on both coal and iron ore mines, demonstrating reasonably accurate results. This study aims to bridge the gap between theoretical blast design models and practical field applications, ultimately enhancing the synergy between blast fragmentation and shovel efficiency in surface mining operations.

Introduction

Mining, an ancient practice dating back about 30,000 years, is vital for human progress and sustainable development. Historically, mining evolved into two main types: underground and surface mining. Underground mining employs methods like room-and-pillar and longwall mining for coal, focusing on stability and productivity, while surface mining is preferred for near-surface deposits due to cost-effectiveness, safety, and larger-scale extraction. The choice between these methods depends on deposit depth, economics, safety, and environmental impact.

In recent decades, mining has expanded significantly with the introduction of high-capacity machinery and advanced technologies like continuous mining systems, improved explosives, and computational tools. Despite emerging rock-cutting techniques, drilling and blasting remain predominant for rock breakage, emphasizing the importance of well-designed blasts to optimize rock fragmentation. Proper fragmentation reduces operational costs by improving loading, hauling, and crushing efficiency, while poor fragmentation leads to extra work and higher expenses.

Surface blast design must balance producing neither too many oversized boulders nor excessive fines, aiming for consistent fragmentation. Current designs often rely on trial-and-error due to geological variability, highlighting the need for systematic, software-aided approaches to improve accuracy and control.

Key parameters in surface blasting include:

• Drill Diameter: Larger diameters improve productivity and reduce cost per volume but require more investment and may not suit all conditions. Smaller diameters offer better control in small-scale operations.

• Bench Height: Must align with drill diameter and loading equipment capabilities to optimize efficiency and safety.

• Burden and Spacing: These geometric factors control rock breakage and displacement, influenced by rock properties, explosive characteristics, and bench design to ensure effective, safe blasting.

Overall, surface blast design combines technical, economic, and safety considerations, often requiring site-specific adjustments for optimal results.

Conclusion

Extensive reviews have been conducted on the parameters affecting surface blast design, leading to the identification of key factors that significantly influence blast performance. Several researchers, such as Langefors and Kihlstrom, Lopez & Jimeno, Ash, Bhandari, Singh & Sarma, Thote& Singh, and Andersen, have contributed to the evolution of various empirical and theoretical blast design methods. Among these, the blast design theory by Langefors and Kihlstrom (1978) is the most widely recognized and applied. Although this approach delivers precise and dependable results, it involves complex and time-intensive calculations when carried out manually.Recognizing this limitation, the need was felt to develop a user-friendly computer-based application that would assist blasting engineers in quickly and efficiently arriving at optimized blast designs. In response, the OCBLASTS 1.0 software was developed, integrating essential design parameters into a structured computational tool. The software interface is intuitive, and the application is easy to operate, even for users with limited programming knowledge.The current version of the software accepts input through the keyboard and enables the export of both input and output data into text files for documentation or further analysis. The software considers a wide range of parameters including rock characteristics, explosive properties, and bench configurations, ensuring a comprehensive and realistic modeling of surface blasting scenarios. Although the software relies on empirical relationships and thus has some limitations in its applicability across all field conditions, it has been successfully tested in two operational mines—a coal mine in Odisha (Orissa) and an iron ore mine in eastern India. The software’s predictions, especially regarding the blasted rock volume, powder factor, and fragmentation size, closely aligned with actual field data, confirming its accuracy and practical utility.To enhance usability and extend functionality, a graphical version of the software was also developed using Java within the NetBeans IDE. This version incorporates a database system, making data handling faster and more efficient. The inclusion of a database also enables users to save, retrieve, and manage multiple design scenarios conveniently, reducing manual input time and allowing for multiple iterations to arrive at the best possible solution.In conclusion, OCBLASTS 1.0 marks a notable advancement in the digitalization and simplification of surface blast design. With continued enhancements, such as incorporating new explosive types, advanced drilling techniques, and modern blasting configurations, the software has the potential to evolve into a highly dynamic and versatile tool capable of meeting the requirements of various mining environments and operational conditions.

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Copyright

Copyright © 2025 Mr. Jaykant Raidas, Dr. Ram Chandra Chaurasia . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.