Truck and Loader Matching - Part 1

For many mines the issue of matching truck capacity to loader capacity is problematic and more often than not results in substantial inefficiency.  As trucks and loading units increase in size the number of passes required to fill the truck is decreasing and the difficulty in attaining the match is becoming more difficult.  The goal of getting the majority of trucks +/- 5% of the rated capacity just doesn’t happen.  Clearly an innovative process is needed.  The first stage in innovative thinking is to benchmark (use data) what is currently being done.

The word benchmark stirs more emotion amongst open cut mining fraternity than any other issue.  It is a polarising issue which people either seem to love or hate.  We, of course, are biased and love it because we have the data.  However, the data teaches us a lot and we think we know what benchmarking equipment can and can’t be used for.  Benchmarking is a widely accepted business tool to identify position and performance against previous performance and the rest of the world.  It is the process of seeking out and studying the best practices that produce superior performance.  Benchmarking identifies your strengths and weaknesses, and to determine strategic areas for improvement opportunity. It shows what can, and is being achieved, (best practice).  The two phases to benchmarking are; determining best practice and how your equipment compares, and secondly,  identifying and learning from leading practitioners?

While we are thinking about truck and loader matching it is worth considering the truck.  Can you accurately benchmark mining trucks? When trucks can work on the surface or lift 400 metres or more; aren’t the differences just too great to gain a useful result.  The simple answer is that so long as you understand the mining scenario and the data you can gain useful information from truck benchmarking.  The total output from a truck (measured as rate multiplied by digging hours) is an important component in the overall productivity equation for a mine.  Then digging hours and the different components of it can be broken out.  The dig rate can be broken into load and cycle time.  Each of these can be broken down further.  The analysis may be as broad or as specific as required.  The key to benchmarking trucks and loaders is to take the “glass half-full” attitude.  What can I learn about areas for improvement?  What are others achieving which I should be able to do?  Many mines are shocked by first time benchmark results and justify it through “But my operation is different”.  These mines are consigned to mediocrity.  Those mines that say “What can I do to improve?” inevitably do improve through the intangible process of simply focussing on performance.  Process improvements come on top of attitude-based improvements.

At the end of a benchmarking exercise a mine will get specific data about their trucks and loaders and surely that can’t be a bad thing.  Remember, your data is your most important strategic resource; so get some return from it.

Compounding the problem of truck and loader matches is the variation in truck and loader performance. It is a simple fact that different makes and models work better than others.  In fact performance varies between makes and models of truck by up to 81%.  This means that the average performance of one model moves 81% more than the average of another model.  (You would sure want to make sure you didn’t buy the bottom one – which is still available!!!)  Clearly a hard rock mine which is 400 metres deep is going to have lower truck productivity than a coal mine where the trucks are being used in prestrip.  However, it should be noted that the difference in average performance for excavator models is up to 66% and that is not dictated by the geometry of the pit where they are working.

Look at it this way.  If you knew your RH340 was moving 13 Mt per annum you might think you were doing OK.  This puts you in the 78^th percentile.  However if you also knew that best practice (~95^th percentile) is 22.8 Mt then you can find plenty of potential.  Surely that knowledge is valuable.

It has been known since the 1990’s payload is the key for dragline productivity.  This has been determined from the strength of the relationship between payload and annual output.  With trucks and loaders there is a much greater dependence on the number of hours the equipment is scheduled to operate.  It is a little perplexing that mines can spend many millions of dollars on equipment and then not schedule to use it.  The best practice mines use their equipment.  They don’t have it sitting around idle.  Consequently, when the piece of equipment is operating, payload is again the key to productivity.

Over the next few weeks I want to investigate this phenomena where trucks inevitably take 2.5 or 3.5 or 4.5 passes to fill.  Equipment selection is still being done very badly and it doesn’t have to be.  More on why truck and loader matching is such a problem next time.

Graham Lumley 

BE(Min)Hons, MBA, DBA, FAUSIMM(CP), MMICA, MAICD, RPEQ