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 78th percentile. However if you
also knew that best practice (~95th 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
