An article in the August issue of World Coal proposed ShovelMetrics™ fragmentation analysis as a solution to the rising cost of pre-strip waste removal in opencast coal mines. Pre-strip waste removal, the process by which massive amounts of overburden material are removed to access lucrative coal seams, has always been an expensive and energy-intensive phase of coal mining. But in an era characterized by depressed commodity prices and the depletion of easily-accessible coal reserves, the cost of overburden removal poses a growing threat to the economic viability of coal mining operations.
It is estimated that strip ratios are increasing at an annual rate of 4%, causing a serious decline in mining equipment productivity and efficiency. To lessen the cost of pre-strip waste removal, coal mines are reducing explosive expenditures by analysing and optimising their blast parameters. Historically, mines have used sieve analysis to assess the particle size distribution of blasted material, but this strategy is prohibitively time-consuming and inconvenient. Image-based photo-analysis is another common method of blast fragmentation analysis but, because it requires placing a reference scaling object on the benchface or stockpile, presents a safety hazard to mining personnel.
New shovel-based, automated technologies like Motion Metrics’ ShovelMetrics™ provide a safer, more cost-efficient alternative to traditional methods of fragmentation analysis. A shovel-mounted fragmentation analysis system can capture data from every layer of the blast to paint a more complete picture of blasting outcomes, and has the added advantage of assessing material before it is further broken down in transport. ShovelMetrics™ is trusted by 50 mines around the world, and can be purchased with other cost-saving features like missing tooth detection, tooth wear monitoring, and payload monitoring.
To test the ShovelMetrics™ fragmentation analysis solution, Motion Metrics conducted a year and a half long study at a large coal mine in British Columbia, Canada. From 2013 to 2014, the mine conducted a series of controlled experiments to find ways to reduce their powder factor without increasing costs or compromising overall shovel productivity. Using the data collected by ShovelMetrics™, the mine determined that they were overblasting and reduced powder factor to increase the average p50 and p80 values by ~20%. They observed no impact on shovel cycle times, and could reduce their powder factor by 5.7 million kg for total savings of ~CAN$10 million in explosives.
Blast optimisation is a key opportunity for cost reduction, and successful coal mines will depend heavily on regular fragmentation analysis to increase equipment productivity. ShovelMetrics™ is among the safest and most accurate fragmentation analysis systems available to opencast coal mines, and can pay for itself in less than a year. Read the full article here.