Productivity and Mine Planning - Part 1

The return from many mining operations has been continually undermined by mine plans which either can’t be implemented or when implemented simply don’t provide the expected results.   There are some amazingly smart, technologically-advanced tools available for mine planning but they are being rendered useless by a poor approach to data and knowledge.  Remember from a previous blog; data is your most valuable strategic resource.  Think about that comment for a minute.  A strategic resource is something you can make money out of.

In previous blogs I have discussed the poor standard of data analysis provided by equipment suppliers and why mines must take responsibility for the really important strategic skill – analysing data.  This blog is about mine planning.

Mine planning is a multi-facetted science.  This simply means that despite the technologically advanced tools there are still multiple places where it goes wrong.  The key driver of this is a poor approach to knowledge management.  We have really, really smart tools and they are hungry for knowledge input, however, at best they are malnourished and normally they are comatose through starvation.  How long has your planning engineer been in the role? How does your mine planning process determine equipment rates?  It is now known that the best practice for large mining trucks is 112% higher than average or best practice for excavators is 168% higher than average, or 124% in shovels or 32% with draglines, etc.  Worse still, the average drill delivers only a quarter the annual metres drilled of the best practice drills.  The data is available but most mines don’t use it.  Despite this huge variation many mine plans assume rates which are higher than best practice and simply have no chance of being achieved. As an example the average dragline in Australia underperformed plan by 7% in 2008.  Not bad, but the average shortfall in coal uncovered was 25%.  Clearly there is something wrong with the planning and/or the execution of the plan.  What is the impact on a mine’s bottom line when the price of commodities are relatively low?  Finally, do you have improvement built into your mine planning and do you have a process in place for the operators to deliver it? 

We have demonstrated the performance of P&H4100XPC shovels in the northern part of Australia's Bowen Basin.  Best practice was 17.9MBCM per annum and median 14.1MBCM per annum.  The project team was under pressure from Executive Management to budget 25 MBCM per annum because in their opinion, “That is what that model is capable of.”  The GBI database indicates the P&H4100XPC shovel is capable of moving 25MBCM per annum, however, only one machine in 40 from around the world will achieve this level and none from the northern Bowen Basin.  In this case the use of 25MBCM in development models would make a huge difference in terms of predicted ROI and approvals for financing but is most likely going to end in the company not meeting their forecasts for the proposed development. 

Now a “competent person” will sign off on this and the deposit will be presented as economic, open cut reserves.  Financiers and shareholders will feel comfortable (they are after all one of the largest mining companies in the world) but industry standards suggest they haven’t demonstrated  economically mineable, open cut reserves.  Maybe they are economically mineable, underground reserves, but they haven’t been demonstrated as economically mineable open cut reserves because the inputs into defining them are extremely doubtful by industry standards.

Substantial underperformance is rife and it will continue to be a feature of our industry as long as mine processes fail to use the knowledge which is available.  This starts with mine planning.  Site planners and mining consultants don’t have the data / knowledge so they are happy to keep guessing.  Why do you think many operators treat mine plans as a joke?  Probably because they are.  Effort is needed to help these amazing, technologically-advanced tools produce exceptional plans by facilitating the acquisition, absorption and application of knowledge which is available and is being generated on a daily basis.  It is about the use of information; and in particular the conversion of that information to knowledge and most importantly – innovation (change) on the ground.

The purpose of this blog is to highlight an area where very simple but extremely useful data exists but many people are not using it. The mining plan requires estimates of productivity and costs which feed into the production plan and schedules.  It is the productivity and costs which are a real key to the DCF analysis but are normally done with minimal input from outside the potentially subjective opinion of the person doing the planning.  However, this information is available in great detail from around the world.  The question is posed, “Why do people not use the information available to improve the outcome?” 

I will expand more on this and provide more specific examples in my next blog.

Remember.......The right data.  No speculation.

Graham Lumley 

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

Productivity prediction – fact or fantasy 2?

It is no wonder our mines struggle with efficiency.  Whose fault is it that equipment routinely falls short of predicted performance?  Mine schedules or new development's mine plans are often not worth the paper they are written on.

Last blog I introduced a spreadsheet provided by a supplier with a prediction of performance of a 62.7 CuM shovel.  

Is it really the supplier’s job to tell you how well the particular piece of equipment will perform on your minesite?  Well….. yes and no.  You would expect them to know how it performs on other sites and this would be valuable input for you to use and relate to your own minesite idiosyncrasies.  Right or wrong they simply do not know how their equipment performs (and the fact that we do know is a major threat to them).  As I said last week, in a perfect world our suppliers would take an interest in after-sales performance but over the last ten years most haven’t.  So long as it is running it is doing OK.

The productivity forecast by the shovel OEM was sent to the mine presumably for planning purposes and I wanted to run through this to show why mines routinely miss production targets.  Last week I looked at the truck capacity and the dipper payloads.  This week I want to look at hours and overall productivity.

The annual hours is an area where you would expect the supplier to have a good idea on performance and I suspect they do.  The problem is that in many cases the hours worked are so low the supplier is probably embarrassed to say what they know.  You see, if there are two suppliers in a tender for a loading tool and one decides to be honest and tell the mine what they really know then they will probably lose the tender.  This is a simple fact. Most mines don’t check information supplied by OEM’s and just simply believe the lies and or guesses.  The end result is that the mine receives two sets of fictitious performance predictions.  Mines only have themselves to blame for this situation.  The data exists and there are people around who do know how to analyse it.

Average work hours around the world for the particular model shovel are 4,599 per annum. The OEM predicted 5,098 (Op hrs * Job Efficiency * Truck Presentation).  They either don’t know (which questions their competence) or they are providing numbers they know are wrong.  500 hours in a year is a lot.  I will look into the reasons why these hours are so low in a future article.

Given the poor performance the supplier is predicting for payload (although given what is happening elsewhere with truck loads being well below the nominated capacity, the average may need to be lower still) and the high hours (relative to other shovels) the end result of 21.8 MBCM places this shovel in the 83rd percentile of performance for this make and model normalised to 62.7 CuM.  Now this is fine and I am sure the mine would love to use this number in their mine planning but if they plan for it and don’t get it the repercussions may be significant.  I understand that the OEM has not provided a guarantee but the mine really needs to know (with some degree of authority) whether the OEM thinks this shovel, working at the particular mine, loading the nominated trucks can perform consistently in the 83rd percentile. Interestingly enough best practice (approx 95th percentile) for this model in the geographic area they are is only 18 MBCM so you work out for yourself if they will get 21.8 MBCM.

Following on from this I revisited another OEM’s calculations for a dragline bucket’s performance this week and saw a much more professional approach to giving the mine something to work with.  In this case the supplier had been given copious data by the mine.  However, the supplier’s understanding of minesite operational issues and a specific data issue still resulted in them arriving at the wrong answer for recommended bucket capacity.  Now this doesn’t seem too bad, except if the mine accepted the recommendation they would have purchased a bucket which was more than 10% too big for the machine.

I can’t believe how difficult this is for the mines!!!  It doesn't need to be.  In this case we had told the supplier that the payloads from the monitor were flawed!!  This is the main reason why we are encouraging mines to not just give their data out to anyone.  You need someone who knows the data and the issues with it.  You really want to come up with the right answers.  We encourage mines to tell the suppliers to contract an independent third party to do the analysis.  At least then the mine can have confidence in it.

Next week I am going to expand further on the issue about mine plans being wrong due to not using real data as their inputs.

Graham Lumley 

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

Productivity prediction – fact or fantasy?

Last column I introduced the productivity paradigm; fill it up and do it more often, and it was my intention to expand on this further.  However, between writing these two blogs a document came across my desk which has caused me to diverge as there are some important data and productivity issues tied up in this document.  I will address a number of these issues in this and the next couple of blogs.

Check out figure 1. 

Figure 1

We are working with one of the major mining companies in the lead-up to them taking delivery of a 62.7 CuM electric rope shovel and a number of 327 tonne trucks.  I will leave the OEM’s names out.  The mining company was sent a productivity forecast by the shovel OEM and I wanted to run through this to show why mines almost religiously miss production targets.  You see many mines will look to everyone except within, to determine the likely performance of new equipment.  Many often turn to the supplier and blindingly accept whatever they are told.  Down the track when forecasts aren’t met there are a multitude of excuses the supplier can use as to why and what has changed since the assumptions were made.  I know because I have helped suppliers get out of trouble for overly-optimistic predictions (and in some cases guarantees) on production rates.  This is not an attack on a particular supplier as they are mostly the same; why would you expect them to know about productivity?  They are equipment manufacturers.  Sure, in a perfect world our suppliers would take an interest in after-sales performance but many don’t.  So long as it is running it is doing OK.  Many mines compound the problem by doing everything possible to operate the equipment as inefficiently as is possible.

Returning to the productivity analysis. The first point to notice is the fudge factors used to arrive at the answer that the client requires.  In this case the required answer for truck payload is 327 tonnes.  So the Dipper Capacity (heaped), swell factor, dipper compaction and fill factor are all variables in the Excel spreadsheet which can be varied to arrive at the target payload of 109 tonnes. 

Here we raise two really important points.  Firstly, does the truck having a nominal capacity of 327 tonnes mean anything and secondly will the 62.7 CuM dipper carry 109 tonnes on average.  Answering these questions in turn.

Does 327 tonnes nominal truck capacity mean anything?  Well yes it does.  It means it is going to carry a lot of something.  But is it going to carry 327 tonnes of something?  Probably not on average.  Average payload for 327 tonne trucks around the world is 288 tonnes (88% fill) while best practice is 299 tonnes (91.4% fill).  This is an issue in itself which I will write on at a later date but we wonder why anyone including a shovel supplier would use 100% of the nominal capacity of trucks when it just doesn’t happen on average.  The simple answer is that while there is plenty of gossip and innuendo people just don’t know.  Maybe you can start seeing the value of data.  The information is available and you don’t have to plan blindly.  OK enough advertising.

The second question; will the 62.7 CuM dipper achieve 109 tonnes on average.  Back in 2001 we reshaped a 44 CuM dipper to become a 48.4 CuM dipper and it carried 111 tonnes on average so a 62.7 CuM dipper can easily carry 109 tonnes, but will a 62.7 CuM dipper of the supplier’s design carry this payload?  Average in-dipper density (payload / capacity) for this OEM’s dippers is around 1.85 t/CuM which would provide a payload in a 62.7 CuM dipper of 116 tonnes.  So in this case they are predicting below average performance achieved by the new shovel?  Why??  Are they recommending the operators won’t need to fill the dipper up fully to average 109 tonnes per load? What happens if the trucks do only carry say 290 tonnes (97 tonnes per pass)?  Again the supplier doesn’t know and is making guesses.  There guesses are as good as most mines' guesses.  But you don’t need to guess.  The data and information is available and you need to use it. 

A further point to this question.  Another supplier’s shovel dippers perform much better.  This other supplier’s average in-dipper density is around 2.05 t/CuM.  So to move the 109 tonne average payload probably needs a 6-8 CuM smaller dipper which weighs say 8-12 tonnes less.  Maybe they could have purchased a smaller shovel or used smaller gears or motors or whatever.   Don’t ever forget that you are using energy to move your spoil and commodity.  Like it or not but the community’s attitude to using energy is not getting better so you can’t ignore efficiency.  The data is available.  You can make informed decisions.  I will return to this specific case of predicted shovel productivity in the next column.

Graham Lumley 

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

Graham Lumley Christmas Lights 2011

Every year Graham Lumley (CEO of GBI Mining) and his family decorate their house for the Brisbane Christmas Lights competition.


We thought it would be nice to share some of the photos from this year!


All are welcome to come and take a look between 7.00pm and 10pm from 1st December - 24th December.


Address: 6 St Clair Close, Parkinson, QLD 4115


Also you can check out the videos on YouTube: 


Christmas Lights 1

Christmas Lights 2

A Productivity Paradigm

I have spent some time looking at the issues relating to productivity and why working hard on a mining solution rather than a “Business Improvement” solution is really important.  You know at the end of the day that the most important strategic ability your mine has is to be able to implement value-adding change.  Also, there is that catch phrase “continuous improvement” which is really, really important when considering the most important strategic ability.  It is interesting when studying data from best practice operations to see the trend of their performance.  In the majority of cases it trends up.  It might be 2% one year, 3% the next and maybe some years it is 0% or down a bit, but the trend is unmistakable.

While Six Sigma, Lean, TOC, etc. are all useful systems, you have to be careful that the improvement you gain is in the removal of your commodity not just the understanding of the “correct” process of business improvement.

However, lets take a step back and assume you are not one of the 10% of mines that has best practice performance of your mining equipment.  Where do you start?  Well the first place you start is in the collection and use of data.  There are monitors for all equipment now and there is no reason not to have one on every piece of equipment.  We have just kicked off a project with Vale in Brazil and they have many, many small excavators and small trucks running around a number of their mines.  From a fleet of 5 m³ excavators and 40 tonne articulated trucks they have a monitor on everything and the data quality is as good as anything in the world.  This is a company which is trying to catch up technology and bring their mines into the 21^st century and they have monitors on everything.  You need to be the same.  It has often been said that if you don’t measure it then you can’t improve it and while this is true it is more than this.  If you don’t acquire it, analyse it and apply it then you can’t improve it.

OK, so we assume you have monitors (and even if you are still to get them) there is a very simple paradigm for improving your equipment.  That is; Fill it up and do it more often.  “Too easy”, I hear you say.  “We already do”, most will respond.  My response to this then is - why aren’t you achieving best practice?  If your P&H4100XPB shovel is moving less than 50 million tonnes per annum or your EX5500 Excavator is less than 24 million tonnes or your Cat 793 truck is less than 5 million tonnes per annum per truck then why aren’t you doing what best practice operations do?  The problem is twofold.  

Firstly, many mines find excuses not to “fill it up”.  These excuses range from, “I can't overload the machine” to “If I don’t fill it up then I can cycle quicker” to “We can’t handle the spillage” to …….  Any of these sound familiar?  Another issue for many mines is that operator have been taught to not fill it up.  The number one, most important thing you can tell an operator is to fill it up.  Irrespective of whether it is a truck, dragline, excavator, front end loader or electric rope shovel the singular directive should be given to the operator; “Fill it up”.  This sounds simple but an operator must be taught what full is and then how to achieve it consistently.  It is surprising how many different definitions there are of “full”.  I will return to this issue of full in future posts as it is a really important concept which many miss.  

Secondly, you must treat every second of time as being important.  This is another one of those attitude issues.  Do you operate your truck for 5,000 hours per year or 6,000?  Think about it this way.  If you could save 15 minutes a day simply by being more efficient in how you park your equipment and how you start it up again (this is one we have actually studied and we reckon 15 minutes a day is the average most mines could achieve per piece of equipment) you would save 90 hours per year.  The key here is attitude towards time.  The average hours worked for a Komatsu 830e truck is 5,159 per annum while best practice mines operate them for 5,675 hours per annum.  Interesting isn’t it.  Now right here I can hear the excuses, weather, height above sea level, hauling profile, etc. but the underlying issue is attitude.  If you found yourself making excuses as soon as you saw those numbers then you need to have a think about your attitude.

Graham Lumley 

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