Haul truck speed analysis: Using data to increase productivity and reduce costs
The majority of today’s mining companies are looking for ways to reduce costs in order to survive in a challenging economic environment. Reductions in commodity prices are forcing mines to find new ways to work more efficiently using the people and equipment they already have.
“Miners need to produce the same amount of material — at less cost — and still keep safety as their number one priority,” explains Metin Yildirim, a technology application specialist for Caterpillar’s Mining Technology Enabled Solutions organization.
Yildirim presented one solution during the recent Annual Conference & Expo (ACE) hosted by the Society for Mining, Metallurgy and Exploration (SME) in Denver, Colorado, USA. In keeping with the ACE theme — The Future for Mining in a Data-Driven World — Yildirim explained how data can be used to increase truck speed and ultimately improve overall mine production and reduce costs.
Setting improvement goals
Yildirim began his presentation with the basics — those key things miners focus on in all of their improvement efforts:
- Increasing availability and utilization
- Increasing overall mine production or, at a minimum, meeting their production targets
- Reducing the costs of maintenance and fuel
“Of course mines want to increase machine availability and utilization,” Yildirim said. “But just because you have equipment available and ready to produce, that doesn’t mean it is being used 100 percent efficiently. It may not be down, but it may not be being utilized for production.”
One of the key ways to accomplish these goals is through optimized haulage — making the loading and hauling process as efficient as possible. Fleet optimization is often measured by queue time and hang time — those times when ore is not being produced because the haulage fleet is waiting in line to load or dump, or caught in traffic and therefore not able to quickly get to the loader or dump site.
“To improve efficiency, you have to control and reduce downtime, standby time and delay times,” Yildirim explained.
Measuring productivity and efficiency
One of the key ways to measure the efficiency of the loading and hauling cycle is through the Ton x EFH / Operating Hour formula.
- EFH stands for Effective Flat Haul, which refers to production in a normalized elevation.
- Operating Hours contains all of the machine activities undertaken in a typical cycle: dumping and traveling empty, loading and traveling full, queueing and spotting.
“Among these activities, most of them are not affected by the actions of the truck operator,” said Yildirim. However, travel times are fully dependent on the truck speed, which can vary due to:
- Operator inefficiency
- Minor stoppages at intersection points
- Reduced speed while following other trucks
- Bad road conditions
- One-way roads
“These are areas where we can make changes that will have an impact on truck speed,” said Yildirim. “What if we could calculate and predict these speed and time losses? We can — and technology can help us do it.”
Using data to improve truck speed
Predicting the flow of traffic is not a new concept; it’s familiar to anyone who uses Google applications when they are traveling. Google uses trends indicated by the GPS in our mobile phones to predict traffic flow. Google processes the location data to calculate speed and live congestion, then uses a predictive algorithm to identify future traffic flow. These predictions previously were based on historical data gathered over time. Today, however, predictions are based on live data from mobile phones.
A similar concept is applied in the mining industry. “Thanks to technology, we have a vast amount of data from our machines already available to be utilized,” said Yildirim. “It’s there for us to analyze.”
Mines that leverage a fleet management system, such as Cat® Fleet, a capability set of Cat MineStar™, have live GPS locations of every machine. This information is stored for several weeks, along with a timestamp, actual speed, travel time, truck name and operator information. “We can see the details of truck cycles at any time — and we can see their speed at any given point,” said Yildirim. “If we analyze this data, we can extract the truck speed information. We can see problem locations and make recommendations about road design and operating procedures.”
Yildirim shared a real example from an open pit copper mine, with data taken from MineStar. Data was mapped to show those areas where truck speed was reduced to a complete stop. “At one single intersection, we saw almost 350 times where trucks had a speed of zero to 1 mile per hour, and over 3,600 times where they were going less than 10.” These intersections required trucks to slow down or stop every time due to stop signs or yield signs that were part of the road configuration.
“We decided that we would try to eliminate some of these stop signs and have trucks just slow down and then proceed,” said Yildirim. “But we had to find a way to do that safely.”
The team first turned to a “speed, distance and time” chart, which shows the correlation between truck speed and the distance away from the intersection where the truck starts to slow down. “For example, let’s assume a truck approaches an intersection area at a speed of 25 miles per hour,” he explained. “If the truck starts slowing down 200 meters before the intersection, it takes 36 seconds to decelerate and finally come to a full stop. Then, it takes another 36 seconds to speed back up to 25 within 200 meters. This means in total it takes 72 seconds to stop and go.”
The data showed that removal of a stop sign would increase truck speed and eliminate some of this lost time — resulting in increased productivity. But how does that change impact safety?
“If a stop sign is removed, how will operators know what to do at the intersection?” said Yildirim. “That’s where technologies like Cat MineStar Fleet and Detect Proximity Awareness come in.” MineStar allows special waypoints to be created leading up to each intersection point. These waypoints are critical in allowing the system to determine which truck should slow down and which truck should come to a full stop.
“The first truck that hits the last waypoint prior to the intersection area gets the right of way to proceed without slowing down. The other truck will slow down but will not need to come to a complete stop, as the system will make sure the intersection is clear by the time it reaches that point,” said Yildirim. “These systems tell the operator in the cab what to do if there are trucks bunched at an intersection, and can warn operators in advance if the intersection is clear.”
Reaping the benefits
The most obvious result of increasing truck speeds is improved productivity. When cycle times are faster, more ore is loaded and hauled per cycle. However there are gains in other areas that make these improvements even more beneficial to a mining operation.
- Less braking means less wear and tear on a truck’s brakes and transmission. This reduces time lost due to maintenance as well as the costs associated with repair and replacement.
- The use of a technology like Proximity Awareness increases the safety of truck operators. In addition to allowing trucks to move safely through intersections, the system sends warnings to operators about other equipment in the area.
- An increased focus on truck speed and the introduction of technologies to the cab can improve operator practices, make them more aware of their surroundings and help them better understand their contribution to the operation. The result is a more engaged workforce.
- When a truck slows or comes to stop, it uses additional fuel as it accelerates back to its original speed. Faster cycle times result in less fuel usage overall.
“When we can run trucks more efficiently, we produce more tons, use less fuel and reduce maintenance costs. And we do it all more safely,” said Yildirim. “There is a lot to be gained with even small improvements — and automation and technology make it easier than ever for us to take advantage of these opportunities.”