GBIData.com Loading Unit Full Sample Report

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GBIData.com Mining Truck Full Sample Report

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Truck and Loader Matching Part 6

This blog I want to present a case study where a mine had a large shovel with 44 CuM dipper loading 218 tonne trucks perfectly in two and a half passes!  (Situation normal for most!) The dilemma, faced by multitudes of mines around the world, is do you put a third small pass in the truck or do you send it away 80% full?

The average payload of the shovel was 85 tonnes.  The original methodology for determining the match was not known but the performance of the dipper was quite good when looking around the industry.  It appears likely that the original aim was to fill the 218 tonne trucks in three passes.  Two passes sent trucks away with an average of 170 tonnes payload.  The decision was made not to put the third pass into the trucks due to the loss in productivity, damage caused to trucks by overloading and the increased spillage. 

The desired average payload was 218 tonnes per truck (109 tonnes per dipper).  The mine had a quote from the OEM to change the boom geometry of the two shovels and provide two new dippers. Quote was for $6M+.

Using a combination of data analysis and physical modelling four stages of work were undertaken with the following outcomes;

Stage 1         Analyse data. Process changes recommended.  Discussions held with operators.

Result - Payload increased to 95 tonnes on average which was in line with best practice dipper performance.

Stage 2         Physical modeling of the existing dipper, the supplier’s recommended dipper and two boom geometries.

Result – Modelling proved accurate.  Modelling demonstrated under-performance of supplier’s recommended dipper relative to existing dipper.  Recommendation made not to change boom geometry.  Recommendation not to purchase new dipper due to substantial under-performance.  Recommendation to test changes to existing dipper.

Stage 3         Physical modeling of changes to the dipper.

Result – A number of changes had a positive impact on payload but none gave enough by themselves to increase payload to 109 tonnes. Recommendation to conduct further testing combining various options to modify the dipper.

Stage 4         Four options were presented which met the target 109 tonne average

payload, (Figure 1).

The mine chose the preferred option with a slight change, engaged a structural engineer to design the modifications and a local business undertook the modifications to one dipper (Figure 2).

End Result    All up cost $350,000, Average Payload 111 tonnes. Value to mine at the time $8M per annum.

Consequently a second dipper was modified for the second shovel. 

All up cost was $470,000 with two dippers achieving 111 tonnes and 109 tonnes average payload. Cash saved on the project >$5.5M.  Value to the mine $15M per annum.

The most important lesson here is that you can’t achieve anything if you won’t have a go.  The four stages here took 18 months and were rigorously evaluated before proceeding, but the key is that they did it and they added real value.

Truck and Loader Matching Part 5

This blog continues to investigate the issue of why many trucks are being perfectly loaded in 2.5 or 3.5 passes.  In this discussion I am looking at rope shovel capacity and why we need so much steel to carry what is often a very poor payload.

How is it possible that best practice in dipper performance provides a payload of 2.16 times capacity but the dominant manufacturers provide dippers which only achieve around 1.70 times capacity?  This is more than 20% less payload for the same capacity and around the same weight of steel.  This rhetorical question actually has a real answer.  It is because the mines don’t care.  So long as it keeps going and is supported when it breaks then that is OK.  Many mines don’t even complain when the loader truck match is 2.5 or 3.5.  To someone who has worked in equipment productivity for over 20 years this is really depressing.

 

Looking at some issues which impact shovel payload.  Firstly, dipper issues which the mine can have some impact on.  The tooth attack angle is really important. Payload increases by around 0.5% per degree as the tooth attack angle is increased.  However, it is not possible to simply keep steepening the tooth attack angle of the dipper due to the interaction between the heel and the bank.  Relative heel wear rises exponentially after about 65 degrees tooth attack angle.  By 70 degrees the heel wear is probably unacceptably high.  Many buckets are in the range 50-55^o and are losing a lot of payload.

The concept of Bail vs Bail-less is a function of where the hoist connection is made to the dipper. The connection of hoist ropes at the rear of the dipper increases payload.  Where the connection is 25% along the dipper the difference is -10% which is significant. 

The width : height : depth ratios as well as teeth arrangements have an impact on payload but there is little impact site people can have on these issues once you have the dipper so I won’t expand on these issues here.

The other side of the payload issue is operational issues.  Many of these can be controlled by the mine.  What is being dug causes variation in average payload by up to 20% in the same dipper. Herein lies a significant issue relating to truck/shovel matches.  It is possible that the same dipper, even on the same minesite, can get differences in payload of 20% simply due to the spoil being dug.  The key to higher payload is the degree of fragmentation.  The highest payloads are achieved in spoil where there is a range of particle sizes; not all large and not all small.  The implication is that payload is significantly enhanced by good blasting practices.

The power made available to the operator has a major impact on payload.  In harder digging, ie. blocky, poorly shot, etc., increased power provides increased payload up to 120% of the standard power level.  In softer spoils the shovel dipper achieves higher payloads at lower power levels.  In summary, it is beneficial (in terms of payload) to increase power to the maximum.

Bench height plays a major role in determining payload.  At any bench height greater than 30% of boom point height a full payload can be achieved consistently.  Similarly, the distance from the face has a major impact on payload.  The variation from cycle to cycle is quite large but a consistent trend is seen for each digging position.  The first few digs have the loading unit very close to the face.  During these cycles the payloads are reduced possibly due to the inefficient application of power to the trajectory of the dipper / bucket.  The payload increases as the face “moves” away from the shovel.  Once the dipper starts having trouble reaching the face the payload reduces quite quickly.   The decision about when to move the loader is not an easy one to get right.  Generally the operator will decide to move the loader when they encounter difficulty in loading the truck in the designated number of cycles.  To optimise the productivity a range of factors need to be considered, including, payload, fill time, another truck waiting, what the face is like.  As a general observation, if the loader is under-trucked, it would appear prudent to move the loading unit frequently.  If the shovel is over-trucked it becomes a multi-dimensional equation as to when the most efficient time to move is.

                                                      

It became evident from a very early stage in the work on shovels that on some loading equipment the efficiency of the bucket / dipper was severely compromised by large voids inside the dipper / bucket (Figure 1).  These voids ranged from 5% inside a backhoe bucket up to 25% inside rope shovel buckets.  The impact of these voids is included in the previously described impacts on payload.

Finally I would direct your attention to Figure 2.  This shows the variation in dipper payload for P&H and Cat (previously Bucyrus), (both unidentified) and VR Mining Dippers.  I have spent my career helping mines be more productive and the VR Mining dipper is the most efficient dipper design I am aware of.  I am aware there are maintenance, support and financial issues to purchasing a dipper but speak to dipper manufacturers, not just the OEM, the next time you want a dipper.

Just so you know: I worked for VR Mining in 1997 and 1998; before they designed this dipper.  GBI has had a number of small consulting jobs from VR Mining over the last 10 years.  I had no input into the VR design.  Neither I nor GBI receive anything from anyone for the comments made here.  They are simply my honest opinion – the VR dipper is the best and the mines are costing themselves a bundle by not looking at it.  Even if the mines used this fact to put pressure on P&H and Caterpillar to do better, the industry would benefit.

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Truck and Loader Matching Part 2

I have seen many examples of trucks being loaded perfectly in two and a half or three and a half passes.  As I said in the last blog, for many mines the issue of matching truck capacity to loader capacity is problematic and more often than not results in a majority of trucks being under-loaded.  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.   

Mines generally use one of five methods for selecting equipment size/capacity.

1.    Allow the supplier to decide.  Suppliers love this because they can sell the mine the same as someone else has received which cuts down their costs significantly.  However, if the mine abrogates their responsibility to run their mine they get what they deserve.  Remember back last year when I discussed the 62.7 CuM rope shovel.  The calculation had fill factors and all sorts of multipliers to arrive at the correct answer.  However, you don’t need to be as cynical as me to be struck by the fact that it was exactly the same dipper being used on exactly the same make and model shovel at a mine about 150km away.  Were they digging the same spoil? No.  Were they using the same bench heights? No.  Surely they were at least loading the same trucks?  No.  A completely different operation and yet (quite by chance?) the supplier came up with the same dipper as being the right size. Mining with a computer is really easy but it rarely provides the answer which will help the mine optimise what they are doing.  Understand this – if you allow the supplier to specify the size of the equipment you will get the capacity which is best for their profit, not yours.  It saves them much design, engineering and fabrication cost if a supplier can simply sell you the same capacity that someone else has.  

   A quick example from the coal mines on suppliers providing the same product when something different was needed.  A mine ordered a dragline bucket from the dominant supplier.  In this case the supplier has about 75% market share and the mine was justified in choosing them.  After doing some computer mining the bucket supplier arrived at 57 CuM capacity.  Once it went to work the mine was very unhappy with its performance as the average payload was about eight tonnes below what they previously achieved and the operators were complaining about it not digging.  We were called in to investigate.  We found the geometry of the bucket was not matched to the geometry of the pit being dug.  I found the exact same bucket had been built for another mine about 9 months earlier and they were very happy with it.  This operation had an average pit depth of 50 metres and the design matched perfectly.  The second 57 CuM bucket was exactly the same as the first but the digging depth rarely exceeded 20 metres.  End result – the mine lost substantial production and potential profitability.  Anyway, back to the other methods of selecting equipment capacity.

2.    Guess.  There are a number of forms which this takes.  Most people in the selection process will create the “truck-loader” matching spreadsheet but will make a number of guesses about key factors on density, fill factors, etc.  Often this process is aimed at justifying a particular capacity to management.

3.    Existing Data.  This is an extension on guessing.  Data is collected on existing performance and this is extrapolated to new equipment.  This is certainly a quantum leap up from options 1 and 2 but can fall down when data is sketchy or non-existent or when different equipment is ordered.

4.    Computer modelling. This is an extension on point 1.  Some suppliers have flow models for simulating material flow into their equipment but while being good for research and development, they are of minimal value for commercial decision-making.  This is due to the models not being far enough advanced to simulate specific spoil (as opposed to generic spoils).  Now I might get howls of opposition from highly intelligent researchers but I have never seen one good enough for commercial decision-making.

5.    Physical Modelling.  In 1977, D.J. Schuring, released “Scale Models in Engineering: Fundamentals and Applications”, Pergamon Press, New York, N. Y.  In this book, he devoted a section to earthmoving in general, (eg. Bulldozers, excavators, etc), in which he confirmed the accuracy of physical modelling in earthmoving applications.  Scale models have been used successfully on dragline buckets and rigging since 1985.  Similar techniques have been applied to rope shovels since 2000, truck bodies since 2002 and excavators since 2005.  Schuring (1977) found that the key to accurate results from scale models in earthmoving was that the behaviour of the spoil was accurately simulated.  

In my next blog I will carry this discussion on and look at the flawed standard being used to determine truck nominal capacity.

Graham Lumley 

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