GBI presents a snapshot of our "Understanding and Improving Truck & Loader Operations" Course

After numerous requests we have put together a snapshot of your "Understanding and Improving Truck & Loader Operations Course" to give you a taster of this 2 day course.

Please contact lea.andlovec@gbimining.com if you have any questions or would like to book into this course.

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

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

Mining and complexity – paradigm, paradox or parody?

I introduced the issue of complexity in my last blog and stated that there is little evidence in open cut equipment production data that “complexity” plays any role in decreasing equipment productivity over time.  This is a controversial view in the mining industry, particularly the large mining companies where increasing complexity has been used as an excuse for falling equipment productivity rates for some years now.

I stated in my last blog;

It is my theory that the corporatisation of the mine site is to blame for the reduction in availability and consequent productivity.  It is the focus on process and not the result.  Managers are often judged on how they do their job, not the end result, and a declining result can be hidden behind exceptional processes.  Part of that change is an increasing focus on safety but not the majority of it.  Because most managers have little real natural management expertise they embrace the processes which are encouraged by corporatisation.  Six Sigma or Lean are great because they provide the manager with a focus on process.  You can actually point to what you have done.  Unfortunately the performance metric is wrong.

I believe that the silent majority support this view but many just have to fit within the confines of the company that employs them.  I received the following from someone running a mine this week after they read my last blog (that makes two of us who read it).

You are so right about people getting hung up about the process of a process and the process of process improvement rather than the bottom line impact of the outcome it produces

You can extend this further by explicitly focussing on added value as the principle and proper measure of improvement. eg "For any given operational outcome, a process 'improvement' that does not measurably generate positive added value or improve safety without negative impact on the firm's overall value is no improvement at all." No matter how exceptional it might be.

This industry needs to take more notice of Prof Michael Porter - the father of the value chain concept. He had it spot on. If it doesn't add measurable value, prune it.  However, remember not all value is financial - reputation, employee wellbeing, and other "soft" forms of value also matter to different degrees in different companies.

Six Sigma and Lean do not cover the value chain concept well I reckon, and their experts too frequently have no wider business management training to know any better.

A few other personal operational observations for you;

• Pits do get more complex sometimes but usually just deeper and/or less "rich". Any complexity is mostly human induced.
• You are right about availability being a function of age. BUT its more complicated and its only true beyond a certain age. There is a trade-off between depreciation of new equipment with age and repair with age on 2 axes vs availability with age on the third. If you map profit (or net value added) against these axes you will find here is a reasonable sweet spot for average fleet age where profit is maximised - and it’s not at any of the extremes. Operational rosters (eg 4 days a week, 24*7 etc) change the sweet spot quite a bit.
• I've never seen any specific mining industry research on this and there are a lot of misconceptions out there.
• Availability is an issue but not the only one. Cost saving pressures, lack of professional knowledge, managerial ignorance and inappropriate performance metrics are an even bigger part of it. Maybe some would argue this is the actual "complexity" causing most of the problems, eg...
• Payload and digging cycle time (esp truck shovel) are affected (often severely) by poor pit design (relative to deposit and equipment), poor road placement, poor matching of blast performance, poor dump design, but also limited communication between the engineers and mining supervisors - the latter usually make the shift to shift decisions with no knowledge or understanding of the former's work (= poor decisions frequently).

I will repeat my last paragraph from the last column.  Commodity prices (maybe with the exception of gold) are going to decline.  You won’t be able to keep making money without focusing on the real reason you are in business.  You need more of your commodity going out the gate at a lower cost, not a new business improvement process every week or month. 

  

Graham Lumley 

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

Truck and Loader Dictionary First Edition Sample

Truck and Loader Dictionary First Edition Sample

Complexity and Productivity

If you were to ask a mining executive why their mines’ equipment performance has reduced over time, apart from spluttered expressions of disbelief from some you would certainly get the issue of mining complexity fairly high in the excuses.  This is because site people use this excuse almost universally when asked why their performance has reduced.  It seems logical that mines dig the easiest / most profitable areas first and conditions do generally become more difficult over time.

When executive management starts holding site people accountable for the equipment performance it is interesting to see what happens.  It usually goes something like this;

1. Dry up the source of the bad news – ie. stop benchmarking.  “We know we are 40% below best practice so why keep telling Executive Management”.
2. Advise management that reducing performance is a function of complexity of the mine. “We know it is getting worse and we know it must be the increasingly complex mine we are running.”
3. Create a picture of how complexity reduces digging hours or increases cycle times, etc.

However, should equipment achieve less output as the mine becomes more complex?  This really is a perfect example of not letting the truth get in the way of a good story.  We have looked at this issue from multiple angles and we can’t find any evidence to support this notion that complexity reduces the performance of a particular piece of equipment.  Even for trucks if you use an appropriate measure of truck performance there is no consistent reduction in performance.  Of course as a mine gets deeper and more complex, more equipment may be needed.  This is a completely different issue.

So let’s look at the truth. 

The absolute key to the performance of any piece of equipment is payload.  I can’t find any logical explanation as to why complexity should consistently impact payload.  The only possible impact could be in bench heights and/or pit layout.  However, if superintendents and engineers do their job there is rarely a reason not to set the pit up to ensure optimised payload.  The differences in payload (eg. The difference between dragline best practice and average is 17% and other equipment is similar) are inevitably caused by other factors.  The most common and most distressing is mines telling operators not to fill up the bucket or truck body and kicking the operator when they do!!!  For heaven’s sake the operator’s job is to fill up the bucket and he/she should be encouraged to do this to the best of their ability every time.  If it is overloaded then don’t blame the operator; this is a management failure.

OK so it can’t be payload.  Is digging time related to complexity?  The key area that gets blamed is operational delays and most specifically waiting on equipment or blast.  We have tracked operational delays and we know that when productivity drops, about 40% of the drop can be linked to operational delays but only about 6% is linked to waiting on something.  So really it has little to do with waiting on equipment or blast.  Yes there is a relationship between complexity and operational delays but the major loss in productivity is found elsewhere.

Often the major contributor to a loss in productivity over time is availability.  What happens is that there are two key relationships.  Complexity increases with time and availability tends to reduce with time.  The truth is the two relationships are only linked in a very minor way.  So is it equipment getting older and harder to keep going?  Maybe, but old equipment does get replaced and the trend does continue.

It is my theory that the corporatisation of the mine site is to blame for the increase in operating delays; the reduction in availability; and consequent reduction in productivity.  It is the focus on process and not the result which is primarily to blame.  Managers are often judged on how they do their job, not the end result, and a declining result can be hidden behind exceptional processes.  Because most managers have little real management expertise they embrace the processes which are encouraged by corporatisation.  Six Sigma or Lean are great because they provide the manager with a focus on process.

A bit of a wake-up call here.  Commodity prices (maybe with the exception of silver and gold) are going to decline.  You won’t be able to keep making money without focusing on the real reason you are in business.  You need more of your commodity going out the gate at a lower cost, not a new business improvement process every week or month. 

Graham Lumley 

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

Recognising Innovation

Australians on the whole are not overly innovative and regularly fall below average in measures of innovativeness across countries around the world.  There is little doubt that this contributes to poor equipment performance.  I noted a little while back where Dr Peter Lilley of CSIRO was lamenting the lack of “transformational” R&D.  I was staggered (although maybe I shouldn’t have been) that the Minerals Down Under group has a budget of $100+ million per year for R&D.  Think about that for a minute.  Over $100 million per year and they can’t come up with some workable transformational ideas?  You have got to be kidding.

A project which my company undertook was one of the outstanding engineering projects which won Engineers Australia State awards and competed for National Awards in Canberra recently.  What a privilege to be amongst some truly transformational engineering.  Our project – Optidrag, had a budget of $276,000 (thank-you to ACARP).  Now Optidrag really is transformational and is being embraced by a number of the major mining companies.

I am sure this industry suffers a serious case of Myopia when it comes to innovation.  Here you have a project which is one of the outstanding engineering projects in Australia in 2009, as judged by Engineers Australia, and the Australasian Institute of Mining and Metallurgy rejected it as being unsuitable for one of their Mining Conferences.  Quite apart from the fact that it is my project and I was prepared to fly across the country to present it in Perth, how can a project recognised by the pre-eminent professional engineers association in Australia as one of the outstanding engineering outcomes in 2009 be not recognised by my esteemed colleagues in the mining industry? 

Sour grapes?  You are joking.  I got to sit in Parliament House in Canberra with the engineers who were recognised as having the most outstanding projects in Australia in 2009.  I happily saved my money and did not attend the conference in Perth but I am distressed for the industry I work in.  I side with Dr Peter Lilley in so far as believing this industry needs transformational change.  However, I believe it is needed in R&D, technology and attitudes.

The biggest problem with research and development in Australia is they are too focussed on the process rather than the outcome.  Tick the boxes, get your government money and if it costs more than budget or you don’t get an outcome then so be it.  Move on to the next project.  Compare that with the private sector.  We are currently developing a new product.  Exciting and terrifying at the same time.  We went to Westpac, cap in hand and asked them to finance a shoestring budget.  They took mortgages over our properties, a fixed and floating charge over the business, personal guarantees by the owners of the company (my wife and I) and security on our souls in case we decide to depart this world (watch out - banks have contacts in high and low places, although not too many above).  If we can’t produce a product when the money runs out we are screwed.  If the product fails to sell we are screwed.  Despite our patent protection, if a big company steals the idea, I can’t afford to fight it for 10 years in the courts – we are screwed.  If a Rio or BHP fund it they will rightly tie it up so not only does nobody else get it, we also can’t do any further work on it.  The research organisations haven’t delivered and small people have incentive not to be innovative.

Transformational changes in technology don’t come along too often.  You can think about draglines, hydraulic shovels, etc as being major advances but they are few and far between.  The thing which concerns me is that sometimes ideas are not advanced for the wrong reasons.  Politics in our large mining companies and our research institutions ensure some truly transformational ideas will never see the light of day.  Consider the following.  After presenting Rio Tinto's automation work to the Austmine conference in Brisbane last May, Rio Tinto's head of Innovation, John McGagh, was asked how we, as small, dynamic innovators could get our products in front of Rio Tinto.  His response was distressing. "Rio have people and resources working in this area.  If you have something of value to us, we will find you."  I really don't know where to go with that.  I suppose it is the golden rule; He who has the gold makes the rules.

I have said much in recent weeks about transformational changes in attitudes towards productivity.  Productivity is largely about attitude.  I fear for Rio's investment in automation for this very reason.  Attitude is the key input into the differences between best practice operations and the other 90%.  Some have given up and accept mediocrity or pay contractors to be mediocre or make huge investments in technology.  Some mines and contractors have grabbed the opportunity and have moved to fill the gap between average and best practice performance.  They are the companies you really want to work for and with.

Graham Lumley 

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