By: Alejandro Huamanchumo, Mine Operations Superintendent and Edwin Briceño, General Manager of Mine Operations, Minera Yanacocha.

Abstract

Payload management is fundamental in the mining industry because it allows to increase production and productivity of material hauling; however, a permanent control is necessary to avoid overloading the gears, which could have negative effects on the operation.

This article explains the strategies and actions taken at Newmont Yanacocha to improve operating results by optimizing hauling costs through improved management by increasing payload on its fleet of 26 CAT 793 C/D trucks. 

The payload project consists of increasing from an initial base of 105% (234 tons) to a challenging 110% (245 tons) to further maximize truck loading while avoiding structural damage to the CAT 793 C/D trucks, reducing maintenance tasks associated with overloading and minimizing material spillage during hauling. 

In this sense, the Newmont Yanacocha mine area worked on five fundamental pillars: (1) Reduction of empty truck weight, (2) Limitation of underloads, (3) Change of target payloads, (4) Elimination of overloads and (5) Calculation of new payload target. Through all the actions taken, we were able to align to Newmont's corporate standard, achieving an average payload of 245 tons (110%) and a savings of US$ 1'635,540 by the year 2021.

Introduction 

In any open-pit mining operation, hauling material with trucks is the unit activity that generates the greatest expense in mining. At Newmont Yanacocha, it represents 45% of its mining costs. According to Hardy (as quoted in Moreira & Marin, 2018): "The importance of the haulage fleet is emphasized, as it corresponds to 38% of the operating cost in open-pit mines" (p. 443).

The current price of fuel, tires, spare parts, etc., have motivated the search for internal opportunities to minimize these costs, maximizing operational efficiency such as payload, truck speed, haul road conditions, operator efficiency, among others.

According to Soofastaei et al. (2014): "Payload has the most significant impact on mine productivity, diesel energy consumption, greenhouse gas emissions and associated costs" (p. 01).

For this reason, Newmont Yanacocha is committed to the payload project based on a joint effort between the Mine Operations and Maintenance areas. This effort consists of improving payload management by involving its leaders and operators, all aligned in achieving this objective: in the Mine Operations area, by seeking to increase the load capacity of trucks to an acceptable tonnage of 5% of the Payload without affecting the costs of maintenance due to damage caused by overloading; and in the Mine Maintenance area, by making an effort in identifying opportunities to maximize the load of trucks by reducing the weight of hoppers with the application of lighter coatings at the base of truck hoppers, which reduces the weight from 2 to 2.4 tons per truck. 

In this way, improvements in fleet management have been implemented to increase payload, thus achieving a higher truck load, without a significant impact on equipment and performance parameters such as EFH and speeds. These efforts were associated with reducing the weight of equipment hoppers and minimizing the number of trucks with loads of less than 95%, achieving an increase in the target payload from 105% to 110%, which represented an increase from 234 to 245 tons. The result of this effort contributed to lower hauling costs.

Newmont Yanacocha has been making improvements in cost optimization by increasing payload; however, it has been observed that there is still an opportunity to increase the target payload to maximize truck load and optimize costs. Therefore, the objective of this study is to show the improvement of operating results by increasing payload.

Background

In 2019, the target payload was 238 tons; however, the actual average payload for the entire year was 242 tons (108.6%). Figure 2 shows that in all months a payload above the target was achieved, allowing an additional tonnage of 1'248,795.8 tons to be loaded in 2019. There were no reports of structural damage to the trucks.

In 2020, the target payload was 238 tons; however, the actual average payload for the entire year was 241 tons (108.1%). Figure 3 shows that in all months a payload above the target was achieved, allowing an additional tonnage of 710,193.5 tons to be loaded in 2020. April is not included because no work was done due to the Covid 19 pandemic; there were no reports of structural damage to the trucks.

Conceptual Foundation

Caterpillar's 10/10/20 Policy

According to Caterpillar (2021), the Payload Management Policy is as follows:

ν 90% of the total loads must be within the range of 90 to 110% of the rated payload.

ν No more than 10% of the loads should exceed 110% of the rated payload.

ν No load should exceed 120% of the desired rated payload.

Causes of under- and overloading

Underload

The main causes identified for low payloads, which negatively impact production and increase the cost per ton, are:

ν Failure in the truck system (balance).

ν Experience and performance of the loading operator.

ν Unlevel loading surface at the mine face.

ν Poor centering of truck loads.

ν Failure in the truck/scooptram communication system, among others.

Overload

The main causes identified for high loads as well as low loads are:

ν Failure in the truck system (balance).

ν Experience and performance of the loading operator.

ν Unlevel loading surface at the mine face.

ν Poor centering of truck loads.

ν Failure in the truck/scooptram communication system, among others.

Truck overload could result in:

ν Spillage of material on the road. 

ν Premature tire failure due to heat or cuts.

ν Increased transmission and brake system wear.

ν Decreased life of the frame and other chassis and suspension components.

ν Increased fuel consumption.

Load distribution

“Overloads will decrease component life, but payload placement can have significant impact as well” (Caterpillar, 2021, p. 09).

According to Caterpillar (2021) the following three types of improper load placement occur.

Load shifted toward the front

According to Caterpillar (2021), a load shifted toward the front will negatively impact:

Front brakes, front bearings, front tires, steering, suspension, hydraulic hoist, body rest pads, and body canopy (p.10).

Incorrect load placement will also result in a weight balance error (VIMS System).

Load shifted toward the rear

When the load is shifted toward the rear, the final drive and rear tires will be negatively impacted. Furthermore, the payload will become unstable and slide off the back of the body (Caterpillar, 2021, p. 11).

As with front-placed loads, this incorrect load placement also produce a weight scale error (VIMS system).

Load shifted toward the side

If the load is shifted towards either side, the final drive, bearings, tires, hoist cylinders, and pivot bore areas will be negatively impacted (Caterpillar, 2021, p. 13).

Description of Improvement Actions

As part of Newmont's fast replication program, other operations achieved a payload of 110%, so the mine team decided to make a second major effort to move the payload curve to the right and improve from 105% to 110% (245 tons), with a strategy that focused on the following four points.

Reduction of empty truck weight

With the support of the maintenance area, we managed, re-evaluated, and reduced the weight of empty vehicles in our fleet to directly increase the payload that can be transported. This involved reweighing the empty and loaded trucks.

Limitation of underloads 

Our loading practices were improved, limiting the number of under-loaded trucks, which increases average payloads and boosts overall productivity.

Change of target payloads 

We worked and coordinated with OEMs to shift target payloads beyond nominal targets, as this can further drive productivity and value.

Elimination of overloads

Loads above 120% were eliminated and loads near 120% were limited to ensure compliance with safety certifications, improve chassis and component life, reduce maintenance costs, and improve cycle times and overall productivity.

These changes were carried out in parallel with a training program for the mine team involved, comprising the following activities:

ν The necessary information on the Payload Project was provided to all levels such as: management, supervision, operators, and dispatchers of Mine Operations.

ν General meetings were held with the entire mine team.

ν Individual meetings with scooptram, excavator and truck operators.

ν During these meetings, suggestions were received from the supervision and operators line, which were essential to achieve the objective.

New Payload Target Calculation

All haul trucks were weighed with the help of Mine Maintenance in order to calculate the new payload target.

Newmont Yanacocha has two types of truck fleets, 793C and 793D. Each fleet has a different weight because they are different models and therefore have different structures, which is why a payload target was calculated for each fleet.

By weighing the trucks, we were able to determine the payload target for each truck according to the fleet, obtaining an average payload target of 223 tons (100%) for the 793C fleet and 219.7 tons (100%) for the 793D fleet; it can be deduced that the 793C fleet carries 3.3 tons more than the 793D fleet.

To determine a payload target for both truck fleets, a simulation was made for each one with targets greater than 100%, in order to find the optimal target without causing damage to either fleet. Finally, it was determined that the optimum payload target is 245 tons (110%).

Improvement Assurance Actions

ν Periodic monitoring and field corrections were made to ensure the correct condition of the trucks' balance and display.

ν Dispatch task observations for real-time payload control by means of VNC display input to truck/scooptram and mine cameras.

Additionally, the Dispatch system has a real-time dashboard to control low loads, high loads, overloads, and load distribution through the Gaussian Bell.

In addition to being able to monitor the payload, the dashboard in Figure 13 can be used to track KPIs such as equipment productivity, availability, speeds and EFH.

The dashboard in Figure 14 is used to keep track of a good load distribution aligned to the intended target, tracking by guard, loading equipment (scooptrams and excavators), operators and truck fleet.

ν Field task observations for loading and haulage operators by the Mine Supervisor, correcting and reinforcing payload management aligned to the new target.

ν Daily, weekly, biweekly, and monthly control and feedback of general and on-call load distribution.

Figure 16 shows a report of the general and on-call load distribution curves, which is done on a daily, weekly, and monthly basis, in order to correct and control low or high loads. These curves are also used as part of the talk given before the start of each on-call shift, to inform operators about the payload project and to improve the distribution of target-oriented loads.

Methodology

The methodology used in this study consists of data collection, processing, and analysis.

Data Collection 

Data was collected on payload per truck and scooptram for the year 2021; such data was obtained from the Mine Operate system database of the Mine Operations area of Newmont Yanacocha. 

Data Processing 

All data collected from the Mine Operate system were processed and analyzed by month, in order to compare such data with what was projected for 2021 and verify payload project profitability.

Data Analysis 

Once the data was processed, graphs were generated to see the average payload per month and compare compliance with the target payload; in addition, the tons gained by increasing the target payload with respect to the projected payload per month were calculated, thus obtaining the savings.

Results

Tons Gained

In this section the average payload per month for the entire 2021 was analyzed to check compliance with the established payload target.

Figure 17 shows that between January and March 2021, the payload started at 107% (238 tons), then between April and June it increased to 108% (240 tons) and between July and December it increased again to 109% (243 tons). Furthermore, all months showed a certain variation with respect to the payload target.

For each month, an additional production was obtained as shown in Figure 18:

Every month has seen an additional tonnage gain as the payload has increased, with November being the month in which the greatest tonnage gain was achieved. In 2021, an additional 851,399.8 tons will be loaded, thanks to the increase in payload.

2021 Savings

As well as gaining tonnage, costs were also optimized, since more than planned was produced without damaging truck structures, reducing maintenance tasks, operating hours, and fuel consumption. Figure 19 shows the savings per month in 2021.

Savings were observed in all months, with November being the month with the highest savings compared to the others, since the average payload was higher. In 2021, savings of US$ 1'635,540.9 were achieved.

Load Distribution

A load distribution analysis was made with 256,958 trips made during the year 2021, where an average target of 245 tons was obtained, which corresponds to 110%. 

Conclusions

The average payload for 2021 was 245 tons, representing 110%, which was in line with the standard of other Newmont operations. Furthermore, the production of 851,399.8 tons over the planned quantity was achieved, with a savings of US$ 1'635,540.9.

Recommendations

1. Before increasing the payload, it is important to analyze the opportunities for improvement in terms of reducing truck weight; for example, an important piece may be removed that could lead to an operational accident.

2. A good control and monitoring of overloads (>120%) must be carried out, as this is a key factor to avoid damaging the truck's structures. Underloads must also be controlled as they can adversely affect production.

3. The personnel involved must be constantly trained on the payload.

Acknowledgements

We thank PERUMIN for giving us the opportunity to share the improvements that are being made in the mining industry to optimize productivity through good resource management.

References

Moreira, A. C., Marin, T. 2018. The impact of payload truck factor use in mine performance reports for an open pit copper mine in Brazil. REM - International Engineering Journal, v. 71(3), p. 443-449. https://doi.org/10.1590/0370-44672017710189

Soofastaei, A., Aminossadati, S., Knights, P., Kizil, M. 2014. Payload Variance Plays a Critical Role in Fuel Consumption of Mining Haul Trucks. Australian Resources and Investment. https://www.researchgate.net/publication/294891387_Payload_Variance_Plays_a_Critical_Role_in_Fuel_Consumption_of_Mining_Haul_Trucks

Caterpillar. 2021. CAT® Mining trucks payload management guidelines including 10/10/20 policy and payload placement.