Smart shovel-based solution

Louise Smyth

During the commodities boom, the mining industry largely ignored the technological advances that have revolutionised the manufacturing and service sectors in favour of simply increasing production using very basic methods, bigger buckets and bigger equipment. Once the downturn hit, the industry found that traditional, low-tech solutions were no longer good enough to ‘get the job done’.

Luckily there are simple yet sophisticated technological solutions available that can help the industry reverse its lacklustre productivity trend. For example, Motion Metrics has developed a sophisticated shovel-based payload monitoring system that can improve the productivity and cost-effectiveness of truck and shovel fleets.

The problem: lagging productivity

Although mines around the world have invested in larger machinery over the years, mining productivity has decreased continually since the start of the millennium. This is not a regionally concentrated trend. Even the advanced mining regions of Australia and North America have shown a considerable productivity decline. In fact, the situation in Australia is particularly dire. According to a report from PwC, the productivity of mining equipment in Australia has underperformed all of its international competitors except for Africa.

The solution: getting the most out of every truck

Mines looking to maximise cost savings should focus on the highest cost units first. Haul trucks have seen the steepest productivity declines among all types of equipment. Despite their declining productivity, haul truck fleets are becoming more important. With global strip ratios increasing by 4% annually and geological conditions becoming ever more complex, the mining industry is unfortunately burdened with an increased dependence upon pre-strip fleets. Improving the cost-effectiveness of pre-strip truck and shovel fleets is more critical than ever.

Pre-strip operations face two major challenges: maximising shovel productivity; and matching that rate to the truck fleet. Shovel operators are often better at the former than the latter. The decline in truck productivity has outpaced that of shovels by a considerable rate. As there is generally a limit to the number of trucks an operation can afford, this leads operators to compensate by overfilling trucks, improving productivity over the short-term, but increasing fuel costs and risking potential structural damage to the trucks over the long-term.

Most manufacturers specify that trucks may only be overloaded by 10%, up to 10% of the time, with no single load exceeding 20% of rated payload. According to PwC’s database, 93% of trucks violated this rule. In response, Motion Metrics has developed a sophisticated payload monitoring system for hydraulic shovels that can help improve payload compliance and maximise usage by avoiding damage, downtime or voiding the manufacturer’s warranty. Using robotics, estimation theory and sensor technologies, the ShovelMetrics payload monitoring system requires a limited number of sensors to maintain and has the benefit of giving the operator immediate feedback on the shovel bucket before loading the truck, something that weigh bridges and truck-mounted systems cannot do.

Knowing the payload prior to loading is the best method for getting the most out of each bucket and eliminating overloads; it is preventative rather than reactive. In a typical open pit mine, each shovel will load a fleet of four to eight haul trucks. Hence, maintenance is more manageable on one shovel-based system than four or more truck-based systems.

How effective is the system?

The ShovelMetrics system was tested in a large African precious metals mine on a Terex RH200 excavator and a fleet of Terex MT4400 trucks with a rated capacity of 220 tonnes. The payload monitoring system was compared to both onboard truck scales as well as a weigh bridge. Results showed that the system’s accuracy exceeded that of the on-board scales and was comparable to the weigh bridge.

Once the system was put into use on the entire fleet, the mine saw immediate operational benefits. Bucket fill improved by ~10%, reducing the total number of buckets to fill each truck. The mine also saw improved payload compliance, reducing the number of overloaded trucks as well as the amount by which trucks were overloaded. Overloads greater than 110% rated capacity declined by 31% and the percentage of compliant loads (95%-110% of rated capacity) almost doubled, from 12% to 22%. Most importantly, these productivity improvements occurred with practically no change in total monthly production. The mine was able to increase shovel productivity and reduce the costs of potential downtime and structural damage to its truck fleet while maintaining its overall production rate.

 

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