CONTRASTING FUEL MEASUREMENT STRATEGIES IN MINING

This post discusses the contrasting fuel measurement strategies in mining. The three most common fuel measurement strategies employed in mining include measuring at time of fill- tank fill measurement, Engine Control Module (ECM) Fuel Consumption Estimations, and lastly, on-equipment fuel measurement.

Cascadia Scientific’s SmartRView™ , is a machine learning and data analytics platform that is unique in the mining sector for its application of on-equipment high accuracy fuel flow meters. 

This blog post describes the approach of on-equipment fuel measurement, and how it differs from ECM calculated fuel consumption and tank fill measurement strategies. 

1) ON-EQUIPMENT MEASUREMENT

Direct measurement of diesel fuel consumption is a challenging task.  Diesel engines are fed considerably more fuel than they consume with the balance returned to the tank.  This oversupply is important as it is used to extract heat from engine components (e.g. Injectors, ECMs) and ensures the engine is never starved of fuel.  It does however significantly complicate fuel measurement which subsequently requires two meters; one to capture the volume of fuel fed to the engine and a second to capture the volume returning.  It is the difference between these flows that constitutes consumption while the unburned fuel is simply noise.  In the extreme case of motoring, fuel throughput can max out while the engine consumes no fuel at all.  Fortunately, most mining engines spend a comparatively little time under such conditions.  Even so, the situation demands extremely accurate meters to ensure the noise does not overwhelm the measurement.   Temperature poses the next challenge.  Since the meters are volumetric, it is important to measure fuel temperature to account for the drop in density which accompanies fuel heating across the engine.

With all these challenges one might ask “why go to the trouble?”.  The answer to this question comes in two parts, and becomes clear when comparing the direct measurement approach against the two most common alternatives described below.     

2) ENGINE CONTROL MODULE (ECM) FUEL CONSUMPTION ESTIMATES

If an engine is electronically fuel injected, it is nearly certain that the computer controlling this process is keeping tabs on how much fuel has been dispatched.  The engine manufacturers construct models that relate the time a fuel injector is held open to the amount of fuel expected to flow across the injector opening.  These models are executed in real-time and add tiny sums to the fuel accumulator value every time an injector is fired.  In general, the OEMs do a pretty good job of it, but as with any model, their accuracy depends on how closely certain design assumptions line up with reality.  Under real world conditions, fuel injectors age and foul, fuel pressures modulate, and cylinders begin to lose compression.  As these changed unfold, the model’s relevance diminishes.  If you were to consider the combined effect of these factors across a fleet of variably aged equipment from a variety of manufactures, you can expect serious shortcomings in both accuracy and repeatability of the ECM fuel consumption estimates. 

Most mining initiatives that seek to improve efficiency and reduce fuel cost are targeting improvements in the range of 0-5%.  The error and variability in ECM fuel consumption estimates render them little use when the targeted improvement falls entirely within the error band.  This is first compelling reason to consider on-equipment measurement. 

3) TANK FILL MEASUREMENT

If accuracy is the undoing of ECM fuel estimates, it is the single greatest advantage of tank fill measurement.  Unlike the fuel that flows through on-equipment meters, all the fuel through a fill station meter is bound for a single destination. In the absence of fuel leaks and theft, 100% of the fuel dispensed to a piece of equipment will be duly consumed.  As an additional benefit, because the amount of fuel fed to a truck is the same amount of fuel removed from the depot, tank fill measurements are helpful for keeping tabs on storage levels.  The downside is that while this approach provides an exceptionally accurate measurement of a very specific quantity: “the amount of fuel consumed by a piece of equipment since its last fill, provided the equipment was filled to the same level on both occasions”… this value does not provide the necessary granularity to target specific characteristics of mining equipment and daily operation.  A typical fueling strategy might see a truck replenished once per day.  Over the course of that day, the truck might complete 50 haul cycles of various lengths, vertical travel, payload, might be operated by 4 or more individuals, idling between 10% and 40% of the time. 

Drawing accurate conclusions about the specific contributions of these factors to fuel consumption with a measurement frequency of once per day is simply not possible.  Tank fill measurement can and does play an important role in supply chain management and tracking long term efficiency trends, however it is poorly suited to evaluate and isolate a variety of the operational factors that contribute to fuel consumption.  

IN CONCLUSION

On equipment fuel measurement is a complicated task, but the combined benefit of high measurement accuracy and sampling frequency, make this approach the best option for pursing data driven efficiency gains in the modern mine.

Cascadia Scientific’s SmartRView platform is unique in the mining sector for its application of on-equipment high accuracy fuel flow meters. Through on vehicle fuel measurement, advanced analytics, and machine learning, Cascadia Scientific’s SmartRView platform empowers data driven improvement opportunities that increase efficiency and production while reducing costs, and greenhouse gas emissions of mining equipment.

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