David Lilly, Senior Consulting Engineer for DynoConsult, a division of Dyno Nobel, presented his research paper entitled, ‘A Statistical Approach to Integrating Blasting into the Mining Process’, at this year’s prestigious 2007 Oxford Business & Economic Conference held at Oxford University in England in June. The paper demonstrates that productivity improvements have been achieved for mining and blasting companies by using a statistical approach to integrate blasting into the mining process.
The blasting and mining processes are each unique and difficult to integrate because the drivers of both processes are interrelated, site specific and statistical in nature. Particular variables in the blasting process include explosive products, blast geometry, geology, structure, weather, safety and environmental concerns. Additionally, the mining process has its own variables that include differing equipment platform capabilities and characteristics, geological conditions and seasonal constraints such as production demands and hours of work. In addition, both blasting and mining are traditionally physically demanding occupations that require working outdoors under strict time constraints, intrinsic safety hazards and on-going equipment problems.
Also, when factoring in regulatory constraints on neighbor relations, health, safety and control of blasting materials as well as the fact that all mine setups are site specific, it is clear how difficult it is to integrate both processes.
Lilly maintains that progress has been made and outlines the initial steps that must be taken to integrate the blasting and mining process. The first step is the expanded use of extensive blasting and production databases. A statistical description and evaluation of significant blasting variables affecting the mining process furthers the integration of the two processes while first principle modeling and development is proceeding. Future work takes the statistical processes in combination with blasting and mining modelling to create real time optimization methods.
Blast vibration and air blast effects are presently accurately simulated and modeled using blast database information. A major hurdle in modeling the effects of blasting upon productivity is that most mines have several blasts on the ground in various locations with varying geologies and the results can often be different when processed at different times. Even so, research, simulations and modeling have identified the major blasting variables affecting the mining process without determining the final results in most site-specific situations in which the variable blasting parameters are not quantitatively related to the results. In addition, a multivariable approach must be used to quantify the relative strength of the major drivers of mining productivity.
Lilly maintains that statistics can be used to create process controls and help visualize the relationship between blasting and the mining process. Variation and changes to blasting parameters can predict the affects upon productivity and product quality. Further, statistical analysis can also be useful in forecasting, evaluation of new explosives, procedures and also, to evaluate mining methods.
(To read the complete paper, visit www.dynonobel.com.)
