PulseTerraMetrix RS Production Benefit Mine management is commonly interested in assessing the potential benefit of how a shovel based payload monitoring could translate into increased production, or through better loading control, a reduced haul truck fleet maintenance cost. This memorandum attempts to address this issue by simulating the potential productivity improvement /haul truck fleet maintenance reduction cost, that can be achieved by installing a shovel based real time payload monitoring system. To perform the simulation, actual data from a PulseTerraMetrix RS (PTMRS) Health, Payload and Productivity management system has be applied. This analysis demonstrates that with an accurate shovel based real-time payload monitoring system such as the PTMRS, Truck Loading Control (TLC) strategies can be adopted resulting in substantial gains in production. The analysis divided into three parts: Effect on production. Effect on maintenance Additional benefits. Effect on Production The ability to achieve higher target loads without exceeding the rated truck capacity is central to the development of a strategic loading practice. Truck overloading has a negative impact on production because of reject loads or reduced truck speed and increased maintenance effort 1. Truck loads are typically measured using on-board truck weightometers. A truck weightometer measures strut pressures to estimate the payload and yields a typical accuracy of approximately 10% 2 of actual load. At the time of loading, friction within the struts substantially interferes with measurement accuracy and consequently the final truck weight may only be reported to the shovel a few minutes after driving away from the shovel. This delay limits operator s ability to quickly adapt the loading pattern to current digging conditions and consequently to maintain a narrow loading distribution and target load. With immediate shovel based payload feedback, strategic loading practice can be achieved and in this sense a shovel based payload monitor can be viewed as a Truck Load Control (TLC) device. In order to estimate the effect of applying strategic loading strategies on production, BMT WBM has constructed a detailed discrete event simulation (DES) model of the loading and haulage sequence of a truck and shovel operation in MATLAB. The model comprised a single P&H 4100XPC shovel and a fleet of 15 CAT 797F haul trucks. The trucks have a nominal payload capacity of 400 tons. A haul road with a profile typical of those found in open cut coal mines was also assumed, i.e. the distance between the 1 If a truck load exceeds 120% of the rated load, the load is dumped and the truck returns to the shovel to be reloaded. 2 If each strut was accurate to ±2.5%, system accuracy would be ±10%.
shovel and dump sites was set to 30 km with a maximum haul road grade of 5%. The model also applies the speed-torque/rimpull curves of the 797F trucks to simulate the effect of truck speed and payload on the overall truck cycle time. The distance between trucks was tracked to ensure a reasonable gap between trucks. The wait time at the shovel and at the dump site, the shovel cycle time, and several other details of the process were accurately modelled and tracked. In order to simulate the variation in different truck loads, a normal random distribution was applied to the dipper pass loads using a mean and standard deviation extracted from data captured through the PTMRS at a client site. Typically, truck manufacturers specify that the average truck payload distribution should not exceed the truck specified target payload, and that no more than 10% of payloads may exceed the target load by 10% or more. More importantly, no single payload is allowed to exceed the target payload by 20%. Overloaded trucks dump their loads soon after departing from the shovel and return to the shovel to be reloaded. Consequently, these loads do not contribute towards production and the time for filling these trucks, dumping their loads, and returning to the shovel is lost production time. This loading requirement is commonly referred to as the ten-ten-twenty rule. Target truck loading strategies in truck and shovel operations are typically described as a fixed number of shovel passes per truck where the number of passes is determined according to the rated payload of the shovel and the rated payload of the truck. For example, a shovel with a rated payload of 100 tons will load all trucks with rated load of 400 tons in four passes. This loading strategy assumes that the target truck load and the standard deviation of the load can always be achieved within a given number of load passes. In reality, operating conditions change and at times, even careful loading cannot achieve the necessary target load. As a result, a Truck Load Control (TLC) strategy can be introduced to reduce the occurrence of low loads without overloading the truck. To achieve this, if a truck load of less than a certain amount is reported during loading (360 tons in this study for a shovel with average pass payload of 97 tons and a truck fleet with a rated truck payload 400 tons), the operator is instructed to apply an additional pass with a dipper that is partially/proportionately filled to achieve the truck target load. In order to apply a smart TLC strategy, the shovel operator needs to know the amount of payload in the dipper immediately after it breaks the bank, so that truck overloads can be avoided by discarding the dipper load if necessary. By providing real-time feedback to the operator, shovel-based payload monitoring systems enable welltrained shovel operators to consistently fill the trucks with a smaller variation in total load. In our simulation, we have considered three different loading scenarios: 1. A simulation of the truck loading distribution before installation of the PTMRS system. For the simulation, an average pass load of 97 tons with a standard deviation in each pass load of 20 tons was assumed. In this case the operator is instructed to always load the truck with four passes. 2. In the second scenario, after installing the PTMRS, the same dipper mean load (97 tons) and standard deviation (20 tons) is applied. However, since the operator receives real-time feedback about the pass load and the truck load, a smart Truck Loading Control (TLC) strategy can be applied i.e. if the truck load is less than 360 tons 3, the operator performs an additional pass with a dipper that is partially filled, proportional to the amount of remaining capacity in the truck 4. If the 3 Using a different minimum acceptable truck load results in slight variation in productivity boost, and this value can be fine-tuned to achieve a desirable loading strategy. Please contact us to learn more about different truck loading strategies. 4 The PTMRS reports dipper load immediately on breaking the bank so that the operator can reject the load before loading the truck. By integrating the system with the mine s dispatch system (Modular, Wenco, Jigsaw) the truck ID and target load can be displayed as well as cumulative truck load and remaining capacity. http://www.pulseterrametrix.com 2
last pass load is sufficient to overload the truck (>440 tons), the load is dumped in the bank and the operator returns for a new load. As a result truck overload is prevented and the consequential loss in production associated with dumping the entire truck load is avoided. 3. In the third scenario, the standard deviation in the dipper load is reduced to 10 tons. This reflects the case of a well-trained operator capable of accurately and repeatedly filling the dipper to capacity. The smaller standard deviation means that the average dipper payload can be increased from 97 to 104 tons 5. Application of a TLC strategy as in the second scenario combined with a trained operator reveals further productivity benefits. The following table summarizes the three loading scenarios. Before TerraMetrix After TerraMetrix (Same After TerraMetrix (Lower Smart TLC No Yes Yes Average Pass Load 97 97 104 Pass Load Standard Deviation 20 20 10 TLC Min Acceptable Truck Load N/A 360 360 TLC Max Allowed Truck Load N/A 440 440 The results of these simulations are summarised in the table below for a simulation time of 36 hours. Before TerraMetrix After TerraMetrix (Same After TerraMetrix (Lower Number of Truck Loads Hauled 594 588 592 Number of Shovel Passes 2408 2547 2400 Number of Truck Loads Dumped Due to Overload 65 0 0 Min Actual Truck Load 272 360 362 Max Actual Truck Load 439 434 430 Mean Actual Truck Load 340 394 398 Total Tonnage Hauled 201749 231736 235462 % Increase in Production 15% 17% In reviewing the result in the table above, it is evident that with the PTMRS active, an overall net production or tonnage increase of 15% can be achieved if a TLC strategy is applied. A better-trained operator can benefit further from the PTMRS real-time feedback and increase the productivity benefit up to 17%. The histogram below shows the distribution of truck loads achieved in the simulations for the three scenarios considered. As is evident in the figure below, by installing the PTMRS and applying a truck 5 Data applied in the simulation reflects actual data obtained from a client site operating a PTMRS system. In this data the most experienced operator achieved a mean pass load of 104 tons with a standard deviation of 10 tons, whilst on average the operators achieved a mean pass load of 97 tons with a standard deviation of 20 tons. http://www.pulseterrametrix.com 3
loading control scheme, all loads below 360 tons and above 440 tons have vanished. As a result productivity benefits can be expected. By installing PTMRS load management system and introducing a truck loading control strategy, the productivity of the same fleet of equipment can be increased by about 15 17%. Effect on Maintenance Lack of a truck loading control system can result in truck overloads, higher haul truck maintenance costs, premature tire failure, rejected truck loads, and higher maintenance downtime, resulting in significant additional production loss over time. This section is focuses on the effect of truck overload on the service life of truck fleet, and therefore the additional maintenance requirement. Production loss due to this maintenance effort has not been directly factored into the simulation, but it is demonstrated that this can be reduced by using a PTMRS system with a TLC strategy. While carrying more payload always results in more damage to the trucks, by using a smart loading strategy we can minimize the ratio of total damage to payload. By providing an instant pass load estimate to the operator, the PTMRS enables the operator to achieve a load distribution with a lower variation (standard deviation) in truck loads. It is noted that the same pass load distribution that was used in the previous section to analyse the effect of the TLC loading pattern on the mechanical damage to the trucks. http://www.pulseterrametrix.com 4
It is widely accepted that the fatigue damage caused by a load is proportional to the applied load raised to the power of 3. As damage is cumulative, the net damage per unit ton of material moved is proportional to, where W i is the weight of the payload in each truck, and W e is the weight of an empty truck. The following table summarizes these values for different loading scenarios in our simulations. Before TerraMetrix After TerraMetrix (Same Standard Deviation) After TerraMetrix (Lower Standard Deviation) Total Truck Loads ( - tons) 201749 231736 235462 % Increase in Production 15% 17% Total Measure of Damage ( tons 3 ) Damage to Hauled Load Ratio ( tons 2 ) % Increase in Damage per Payload 1.7e+11 2.0e+11 2.0e+11 844e+3 850e+3 855e+3 1% 1% The table above shows that after installing PTMRS, although a productivity boost of 15-17% was achieved, the damage per payload carried has only increased by approximately 1%. Note that if reducing the damage to the truck is the most desirable outcome, a different loading strategy can be designed to achieve a lower damage while maintaining the same level of production. Contact us to learn more about alternative loading strategies appropriate to your operation. By giving immediate feedback to the operators, PTMRS prevents overloading of the trucks, and can prevent an increase in truck damage while increasing productivity, or reduce truck damage by up to 10% while maintaining the same production level. Additional Benefits In addition to the savings in production and maintenance costs, implementing the PTMRS system provides mine personnel with some additional benefits. Some of these benefits are: Continuous measurement of wear to structural members and identification of extreme events allows the mine to regulate maintenance intervals and maximize shovel availability. Discreet, time stamped classification of shovel states provides a basis for measuring operator efficiency. Automated statistical analysis of these metrics with periodic reporting gives management tools to improve operator performance and mine planning. Payload information and structural health can be used as an indication of operator effectiveness and digging conditions. Optional system enhancements such as operator feedback to prevent dipper stall and condition monitoring of rotating equipment for predictive maintenance. Frequently Asked Questions Q: What if the fleet composition/truck model/road conditions/ in our mine is different from what is used in your model? A: We have tried to use parameters that are similar to a typical mine site, and we believe that normal variation in these parameters will not change the fact that implementing Pulse TerraMetrix RS system will http://www.pulseterrametrix.com 5
result in improvements in the operation and reduction in costs over time. However, BMT WBM is willing to perform an assessment of your mine condition and deliver a customized Discrete Event Simulation model based on that. Q: What is the advantage of your system over truck weightometers? Immediate pass or total truck load feedback cannot be achieved by a truck based system because the measurement is based on strut pressure which can be significantly affected by strut friction. As a result, although some systems report truck payload at the shovel, these results are often in significant error and the system recalculates the load once the truck has travelled about 500 m from the shovel. This results in a delay of up to three minutes between truck dispatch and an accurate truck load being reported to the operator. By this time the operator has almost competed loading the next truck and consequently a TLC strategy cannot be implemented. Also, maintenance of the PTMRS system is easier, as only one system requires maintenance as opposed to a system on every truck. Proper calibration of the truck based weightometers requires approximately eight hours per system and requires periodic evaluation against ground load scales. More importantly, with a shovel based system a TLC strategy can be implemented, providing the operators with immediate pass and truck load data. This allows an operator to modify their loading practice in lower density material, perhaps adding an additional pass to maintain and achieve the set target load, or by reducing the bucket fill in more dense material so as to avoid truck overloads. Because density can change rapidly, this information allows operators to quickly learn and adapt to changing operating conditions. Q: What is the advantage of your system over other shovel-based load monitoring systems? While several other load monitoring systems use electrical parameter or hybrid models to calculate the dipper payload, the PTMRS uses a unique load cell approach for measuring the payload that is capable of considering the dynamic effects in its measurements. It provides us with a more accurate measurement that is robust and does not require frequent recalibration. Figure below shows the results of two separate independent tests performed by two different mines confirming the accuracy of the PTMRS system. The average absolute error achieved in these tests was 2.04%. Contact us to learn more about the independent tests performed by mines on the accuracy of PTMRS system. PTMRS is also the only system that can measure the carryback in the dipper. http://www.pulseterrametrix.com 6
Q: What is the function of the PTMRS Server? The PTMRS server database collects all system information allowing the mine to define useful KPIs for the purpose of assessing the effectiveness of their operating strategies. Aside from assisting clients to implement specific KPIs, advanced training is provided for the mine staff and operators responsible for maintaining/using the PTMRS system. Q: Can the PTMRS System be integrated with the mine s dispatch system? The PTMRS can be fully integrated to third party dispatch software systems (Modular, Wenco, Jigsaw etc.). Following successful field tests and comparisons between PTMRS and several other load monitoring systems, several mines have adopted the PTMRS system as a gold standard, replacing previously installed indirect parameter/electrical parameter load monitoring solutions. References are available upon request. For more information on the PulseTerraMetrix RS system, contact: Charles Constancon +1 604 683 5777 charles.constancon@bmtwbm.com http://www.pulseterrametrix.com 7