Newcrest Mining Limited is one of the world's top 10 gold mining companies and currently Australia's largest gold producer. Newcrest's Cadia Hill mine, the second-largest open pit gold-copper mine in Australia, produces approximately 300000 ounces of gold annually.
But its low-grade ore requires costly bulk mining and treatment techniques. Newcrest applies the Six Sigma quality improvement methodology and Minitab Statistical Software to keep the Cadia Hill facility running as efficiently as possible, and to safeguard their prominent role in the gold industry.
Processing ore
Many times per day, a fleet of large haul trucks descends a narrow ramp to the bottom of the Cadia Hill open pit, where each truck picks up an average of 225tons of ore to carry back up the ramp to a crushing machine for processing.
The speed of the loaded trucks ascending the single-lane ramp varies from 8 to 14 kilometres per hour.
Slower trucks, of course, take longer to deliver their payloads to the crusher. Even worse, each slow truck delays all the trucks behind it, hampering the performance of the entire fleet and resulting in a serious loss of productivity.
Newcrest Mining tasked Six Sigma Black Belt James Kovac to reduce that variability and increase the average speed of the ascending trucks.
Kovac and his project team began by identifying the variables that might affect truck speed. They collected data to determine which factors had the most impact, using Minitab to plan their data collection process, determine the sample sizes they needed, and test their statistical hypotheses. They then selected five trucks for on-board data collection.
Collecting data
Team members rode along in the trucks over a two-week period, collecting intensive data using laptops, GPS units, and other equipment.
They determined that two factors had a major impact on truck speed: the slope of the ramp, and the trucks' fuel injectors.
The team now began testing solutions - and confirming their results. They altered the grade of small sections of the haul ramp, then measured truck speeds over the altered sections.
Comparing the before-and-after speeds with Minitab's 2-sample t-test showed that the grade adjustments increased truck speed significantly.
The team also devised a clear way to identify faulty fuel injectors. They ran each truck at 700rpm and measured injector timing between all 16 cylinders. Then they switched off each cylinder in turn, leaving the other 15 to maintain the 700rpm.
If the remaining cylinders were not significantly affected when one was switched off, that cylinder was underperforming and therefore needed a new fuel injector.
The test has now been incorporated into fleet maintenance procedures at the gold mine, using control charts produced by Minitab macros to quickly display results.
Results
Minitab's statistical power and easy-to-understand graphics helped Kovac and his team make significant strides in boosting productivity at Newcrest's Cadia Hill mine.
Using Minitab to plan its experiments and analyse its data at each step, the company proved that reducing the grade of the haul ramp from 10.22 to 9.9 per cent in the test section resulted in a 2.6 per cent increase in truck speeds, and reduced variation in truck speed by 7 per cent.
Now the entire haul ramp is being checked and improved, and any sections with a grade of more than 10 per cent will be reduced to 10 per cent or lower. This adjustment is predicted to save at least 8.3seconds per full uphill trip.
Fuel injector analysis
Minitab's analysis of the team's fuel injector data also revealed that 10 per cent of the fleet's trucks were not operating at their peak.
As part of developing the new procedures for identifying and replacing faulty fuel injectors, the team found that replacing one injector in one truck improved cycle time by 5.6 per cent, enough to result in one extra trip out of the pit per truck per day.
These improvements are now making the Cadia Hill Mine more productive, and much more efficient. Newcrest Mining anticipates that it will save more than $835000 in just the first year of implementing these changes.
Minitab Statistical Software originally developed in 1972, is the software used most often in Six Sigma, the world's leading quality improvement methodology.
More than 90 per cent of companies in the Fortune 100 use Minitab, and virtually all major quality improvement training and consulting organisations use and recommend the company's software. In 2007, Minitab received the Customer Value Leadership award from Frost & Sullivan, the world's leading growth consulting company.
Enter X at www.engineerlive.com/ape
Eston Martz is Senior Creative Specialist with Minitab Inc, State College, PA, USA. www.minitab.com