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

A Productivity Attitude

The primary aim of these articles is to get members of the mining community to think about productivity.  Productivity is about attitude.  Much can be learnt about the theory behind operating different pieces of equipment and improving productivity but if the mine does not have a ‘culture of productivity’ then achieving best practice is virtually impossible.  Being innovative helps but just doing the simple  things well is a really good start.

The profitability of many mines is highly leveraged against the productivity of the major earthmoving equipment and thus significant management effort should be focussed on getting the most out of this equipment.  Unfortunately exactly what this entails is not always well understood and often other activities are given preference sometimes to the detriment of equipment productivity.  The actions of mine planning, blasting, scheduling, maintenance and man management all play a significant role in production but need to have a common productivity focus or else they can negatively impact the equipment performance.

Figure 1

Figure 1 is the way many mines are run.  The processes in running the mine and the requirements of the corporate entity simply work against getting optimal performance.  In addition, people with an innovative attitude soon get put in their place and drowned within the bureaucracy.  People on these mines are too concerned with ticking career boxes and making sure the processes are all in place, but when it comes to doing something there is always a good reason not to.

Figure 2

The productive mine (Figure 2) shows a different flow of “impacts”.  We now make the equipment productivity central to the mine’s performance, (which is exactly where it should be…surely).  People and personalities become less important and the requirement for equipment productivity becomes of primary importance.

The equipment productivity is now “driving” other aspects of the mine operation.  It is no longer acceptable for mine planning to impact productivity negatively; they know what is expected of the equipment and they produce plans which help the equipment achieve it.  Blasting, scheduling, maintenance, management, etc. are all the same.  The mine has an expectation of performance (which I believe should be dictated by what best practice machines achieve) and every role within the mine should be singularly focussed on helping the mine achieve the required productivity.  We have inevitably found that this is the way which mines achieving best practice operate.

There is a saying along the lines, “the best things in life are free”.  I find it hard to forget as I had to debate this in Year 10 English.  I now prefer to say that the best productivity improvements are free (or nearly free).  Productivity is about people and attitude and it costs no extra for a mine to have a “productivity attitude”.

I have referred previously to Robe River Mine and the upheavals which took place in 1986 under the guidance of Charles Copeman.  At the end of the resources boom which commenced in 1977/78, mining companies were starting to tighten their belts.  Unfortunately this belt-tightening was resisted by workforces which had become accustomed to getting things their own way.  This attitude was promoted by management which made money despite themselves.  Robe River was the first to face the prospects of an extended “difficult” period by attempting to change the attitude of the mine.  I suspect Charles Copeman knew where it would lead as changing a culture is not an easy thing to achieve.  When change did not come Copeman sacked the management team and installed “his” team of people with the attitude he wanted.  Copeman recognised that change had to start at the top and work its way down.  Sure, it did eventually work its way through and the workforce was sacked and then selectively reemployed some on significantly different working conditions, but the important lesson to learn here is that the change started with management.

This was the start of the depressed period I call the “Downsizing Period”.  It ran from about 1986 – 2001.  I remember one day going on to a mine site (1996 I think) I often visited which had a big sign out the front.  Employee numbers usually ranged from 380 – 400.  This day, the number was 196.  I had to look at it a couple of times but it made an indelible impression on me.

The mining industry has now entered the next difficult period.  Forget the super-cycle or a quick rebound.  The largest economy in the world is bankrupt as is the Eurozone and demand for goods will remain depressed so demand for commodities will remain depressed.  I believe this period will run at least 12 more years (probably longer).  Most mines are now like the proverbial stone which has had the blood ringed from it when it comes to people.  You just can’t keep cutting people and keep the mine going.  Once Executive Management and Boards of Directors realise that prices are coming down they will have no option if they want to stay in business but to chase improvements in equipment productivity.  I wonder if they will follow Charles Copeman’s lead and start with mine managers who accept mediocre or average performance (in this case of their equipment)?  Most operators’ jobs are safe because most of them actually want to do a better job and just need management to help them achieve it.

Graham Lumley 

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

When to spend on innovation

I have introduced a number of broad-based productivity issues over the last few blogs.  We will get on to some more specific issues but in this piece I want to introduce another broad issue.  What is the best time to invest in productivity enhancement?

The two key areas to productivity enhancement are during the R&D / equipment selection phase and during the post-commissioning phase.  That is, get the right equipment and optimise its use.

To understand the interaction between mining and knowledge I will return to the presentation by Jari Kuusisto presented to the Smart Innovation Festival in Brisbane in May 2008.  Kuusisto presented the curve of ROR vs Product Life Cycle.  I have added the risk and cost benefit to this to provide the following plot.

The product life cycle can be described from the mine or the supplier’s perspective.  In the plot here it is viewed from the mine’s perspective.  The mine follows a process of Correct Selection – Order placement – Commissioning – Equipment Enhancement.

The rate of return on money invested is highest during the development / selection stage of the product and during the after-sales service / equipment enhancement phase.  However, the risk on the investment is highest early in the process and reduces further after the product has been delivered.   When these two plots are combined it can be easily seen that the cost-benefit (return / risk) is moderate at the start of the process (during R&D / selection) and highest after delivery/commissioning (during the process of “asset optimisation” or “capacity utilisation”).  It is no coincidence that the application of knowledge is needed most during these two sections.  It can therefore be deduced that the input of knowledge is related to cost benefit.  It is also interesting to note that the highest cost benefit occurs when the knowledge is applied in the after-delivery phase of equipment optimisation which is largely process related.

If one looks at this from the perspective of a supplier the product life cycle  becomes: R&D, Collect Orders – Commissioning – After Sales Service.  Interestingly, the plot follows exactly the same form.  For the equipment supplier their greatest return comes in after-sales service.  This is a really interesting observation because during the boom I had an almost impossible job getting suppliers to listen to anything to do with knowledge and after-sales support.  Suppliers apparently were able to sell all their equipment and the concept of using after-sales service and knowledge as a means of helping mines use their equipment better and as a point of strategic advantage wasn’t considered.  This has clearly changed.  I have had a number of companies approach us about using the data and knowledge as a key element in their marketing strategy.  During the boom nobody seemed to care that there was one brand of truck which was 84% more efficient than the worst.  Funny isn’t it?  During the boom if it had wheels and carried dirt it was good enough.  Now a lot of mining people don’t seem to want to take the risk that they will buy the worst truck and some suppliers seem motivated to use data to help them be as good as their equipment allows them to be on the mine sites.

It seems prudent for suppliers to understand the words of S. Downton on ecustomerworld.com,

Delivering high levels of customer satisfaction through a well-managed service operation can increase loyalty, and thereby sales, by as much as 8 times - greatly enhancing the value of the business. Successful manufactures increasingly focus on their customers' total lifecycle by investing in their service management business to maximise the value captured throughout the product lifecycle. This means that the product sale is only a small part of the overall value during the complete product lifecycle and is only the start of the customer relationship.

Support for my belief that the world of suppliers has changed came late last year when we found a bucket manual which I had written for a mine to optimise the performance of the bucket they had just purchased, had been blatantly plagiarised by the OEM and presented to other mines purchasing their product under their name and logo.  This supplier has seen the value of knowledge (particularly linking the knowledge to the company) and has seen it as providing strategic advantage for them.

Graham Lumley 

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

Knowledge Intensive Mining

I have addressed the issues in the previous couple of blogs about the poor use of knowledge and value adding through innovation by the Australian mining industry.  I have been quite negative about how the Australian mining industry is performing in this essential area.  So rather than always be negative, the aim of this discourse is to describe a process and a culture which will form the foundation of improved performance through knowledge-intensive mining. 

With some hesitation I return to University and 1^st Year Chemistry.  We consider a reaction with a desired result.  The chemical reaction requires reactants and a catalyst.  To achieve the desired reaction (adding value through innovation) we need the correct reactants (processes) and catalyst (culture)

If you knew that there was an M8050 dragline that achieved 21 MBCM annually (17% higher than the next best), would you want to know how? If you knew there was an EX5500 excavator which achieved 12% higher than the next best, would you want to know how?  Most people do and this type of broad information is the foundation of knowledge-intensive mining (but it doesn’t stop at the broad-based information).  The following definition is proposed for Knowledge-Intensive Mining:

Knowledge-intensive mining is the acquisition (from internal or external sources); absorption (through active understanding) and application (via systemic processes or one-off projects) of knowledge which improves the mining process. 

The steps to gaining the tangible improvements, whether they be due to a change in the machine or mining process, must be preceded by a number of steps of gaining the intangible knowledge. Each individual needs to be accountable for their own attitudes and actions, regardless of their position.  Not everyone keeps detailed records of everything he/she does, recognise some form of sub-optimal result, does something different, etc.  What is needed is people doing business improvement on a “micro scale”.  What that means is when a person sees something happening which is sub-optimal they immediately do something to change it.  For an operator an example might be a half full bucket or poor positioning on a block.  Improving this doesn’t take a BI program but if you look at it, a very similar (undocumented) quality / six sigma / lean process is taking place.  To achieve these gains you don’t need a BI program, you need a focussed and motivated workforce / team.  To get this you need the processes and the culture.  Each person up the management line, Operator, Foreman, Supt, Manager, General Manager, etc. needs to take this micro approach to business improvement and it appears clear that many are not.  All too often the upper level manager is too concerned with “ticking the boxes” and / or not making a mistake to worry about really using knowledge to achieve innovation.  After all, their performance is normally judged on how many mistakes they have made, not how innovatively they have acted.

Whether work is in coal mining, hard rock mining, infrastructure, environment, or wherever, the messages are the same:  Firstly, the idea that only tangible things add value must be changed.  We must value knowledge.  We must actively acquire knowledge, absorb it and apply it to add value through modifying processes.  Remember, processes are the innovation reactants.  They are the aspects which combine to produce productivity. 

Changes to them are sometimes hard to grasp or understand but they are none-the-less the fabric of performance.    Secondly, culture is the innovation catalyst.  Not change for the sake of change but rather change which is targeted at the bottom line.

So what do we do about culture? This is the more difficult question at all levels of the mine but if we look at management there are two key issues to do with culture.  Firstly, the attitude of rewarding people who don’t “stuff up” must be changed.  If you aren’t allowed to be wrong then your employer won’t ever achieve anything.  Companies must reward people who are prepared to take measured risks even if those risks fail.  Anecdotally, it is smaller companies which encourage innovation but they don’t always respond well to failure so their support of innovation is not always useful.  If you are rewarded for not “stuffing up” or if you work for a company which describes itself as a “fast follower” then find another company which encourages innovation.  Secondly, you must believe you have a right to be wrong.  If you as an individual aren’t prepared to be wrong then you won’t ever achieve anything.  Unfortunately our education system, which I admire greatly (I am married to a teacher who I met in a small town in the middle of nowhere), encourages people to be right.  There is little encouragement to be innovative and get it wrong.

It is these attitudes (or lack of them) which is strangling the advancement of the Australian mining industry.  

Graham Lumley 

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

GBI Dragline Dictionary V2 eBook - Sample

GBI Dragline Dictionary V2 eBook - Sample

Top 20 Dragline Best Practices Manual Sample eBook

Top 20 Dragline Best Practices Manual Sample eBook

From knowledge to innovation

In my previous blog I discussed the creation of knowledge and adding value through change (innovativeness). The big step forward which is needed for the mining industry is a better understanding of the link between knowledge and innovation.  The innovation process has four characteristics.

1.       Being part of the global world.  Knowledge is everywhere and there is good work being done around the globe.  For example, Europe is not renowned for mining knowledge (although maybe Russia and several of the former Russian States may be exceptions).  Many of the European countries fall in the top quartile for innovativeness and as such frequently have developments of interest here in Australia.  In addition to a number of large equipment companies from Germany which are doing some good work, there are real technology advancements coming out of Europe.  The Vienna Test System which comes from Austria has tremendous application in the Australian mines for operator selection; significant electrical advancements are being made in Germany and tested on draglines in Estonia; etc, etc.  Mines should be grasping knowledge and/or developments from anywhere they might come.  As a primary consideration they should be benchmarking wherever possible.

2.       Innovative individuals and communities.  The mining industry needs innovative people.  I have mentioned it before but the perfect example is the Australian Coal Association Research Program which distributes over $10M annually of the industry’s money for coal mine research.  This program draws some of the smartest and most innovative thinkers into the coal industry research and development arena.  To ACARP’s credit, they do get the whole concept of knowledge development and the link to innovation and have a clear focus on adding value.  AMIRA also plays a vital role for the broader mining industry.  Mines need to build an innovation culture where change is not done for the sake of change but rather to add value.

3.       Systemic Nature.  Being innovative is not something which can be turned on and off.  It is the culture; the way the people think and act.  Some people believe it is difficult being innovative within a large mining company.  This is because they are thinking on too large a scale.  Too often we think that multi-million dollar projects such as Universal Dig and Dump, equipment automation, etc. are required to be innovative.  However, knowledge intensive mining and being innovative can be done on a micro-scale.  Each person can take responsibility for themselves and can follow the path of acquiring, absorbing and applying.  On a micro-scale the operator who, having difficulty loading one bucket ends up with half a load, actively changes their digging for the next cycle and the one after that has applied knowledge. As a summary, each individual being innovative relies on how they are acquiring, absorbing and applying the knowledge which is available.

4.       Customer and user-centric.  This is what I call “bottom line” service.  From the provider’s perspective, knowledge and service provision must be focused on what the user / mine needs.  All too often the mining industry funds work by research groups and consultants, which focuses on the process and how smart the process and people are.  For knowledge to be valuable and to facilitate the innovation process it must be value-based, ie. it must provide bottom-line / profitability improvements for the mines.  The key to this is the person pulling the levers or turning the steering wheel.  This person has the ultimate control over what output is achieved.  Therefore the mine must engage the operator / driver in the optimisation process. 

In the European Innovation Survey, Australia fell in the third quartile.  We are below average in innovativeness, and by industry standards the mining industry is very conservative.  In fact, I could name quite easily those mines in Australia which I consider to be genuinely innovative.  The reasons for this are quite clear and I will address them in my next blog.

Graham Lumley 

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

Improving Equipment Performance – Knowledge & Innovation

The two steps in business improvement for any process, including equipment performance, are to gain knowledge (about gaps in performance) and to do something with the knowledge (innovation). 

There are a number of generators of knowledge.

• R&D which needs policy to support R&D and money to do the R&D.  The money attracts smart people to do the R&D.  A really good example of this has been the ACARP program in the Australian coal industry.  $10M+ of funding is available per year and some of the smartest researchers have been attracted to this money.
• Experience from time on the piece of equipment.  The knowledge is gained from the interactions between the people and their environment.  
• Training which is defined in terms of the content and the delivery / instruction generates knowledge for the trainee.
• Information, which is generated from data, becomes knowledge when it is meaningful to the recipient.

Experience happens, data is collected and benchmarks done, training is provided and research is done by various organisations, however the transition to knowledge is not always done well.  Many have said, "If you don’t measure it you can’t improve it", but it is more than this.  If you don’t actively acquire it, absorb it and apply it, you can’t improve it.  Internal knowledge resides in the people and the captured data.  External sources may include trainers, researchers, consultants, market intelligence, etc.    

The effective generation and use of knowledge is being stifled at the majority of Australian mines.  Good management doesn’t just put red lines through a whole heap of budget items.  Good management is about cost optimisation in the short, medium and long term; not necessarily short-term cost minimisation.  Cost optimisation always allows a budget cost (usually relatively small) to become smarter and practice real continuous improvement.  If an organisation wants to stay operating during the difficult times ahead they really need to spend some money to save more.

The expansion of knowledge and the use of knowledge has attracted the attention of many key mine people, however, the further one looks up through the corporate ranks the less appreciation for the value of knowledge is apparent.  Many people in decision-making positions, struggle with grasping something which is not tangible. 

Most Australian mines fail to take the steps to innovation.  Getting a benchmark or a consultant’s report or a mine plan demonstrates that the manager is doing something.  But really, if something practical isn’t done with it, all he/she has done is waste the company’s money in an attempt to make themselves look good and tick their career boxes.  Without taking the step to innovation / change, nothing of value is achieved for the mine.  A culture has developed whereby not taking risks is rewarded.  "If you want to get ahead don’t stuff up".  Add to this the personal issues many Australians have to being wrong and you can see why innovation is so difficult for some mines. 

The easiest way to use knowledge and to add value is through using data to evaluate and understand what is currently happening and to change based on the knowledge of what others around the world are doing.  It is not about the creation of a simple one-page report from the monitor because chances are that it has been written by an IT person with limited knowledge of what is meaningful.  It is about the active creation of meaningful reports and a program of helping the recipients understand and plan to be better.

Gaining Competitive advantage from Data

In this discussion I intend to discuss how the vast amounts of data which are generated on mining equipment can be turned into productivity, profitability and ultimately competitive advantage.   This is what I call “bottom line” services. 

There is a wealth of valuable mining data being produced around the world every day, however, mines are failing to benefit from it as they don’t have the ability to capture and meaningfully apply it.  Through poor management of available data and the loss of personnel, the continuity of information acquired and knowledge applied to run mines efficiently is being broken. If not remedied, this will prove very costly in the long term.

Data by itself is just a mass of numbers - it needs to be analysed and assessed to extract value. However, mines must be wary of subjective analysis which is done for the benefit of another party rather than the mine itself. All too often the mining industry funds work by research groups and consultants which focuses on the process and how smart the process and people are.  For knowledge to be valuable and to facilitate the innovation process it must be value-based, ie. it must provide bottom-line / profitability improvements for the mines.  The key to this is the person pulling the levers or turning the steering wheel.  This person has the ultimate control over what output is achieved.  Therefore the mine must engage the operator / driver in the optimisation process.  To do this they must have an intimate understanding of the information being provided through reporting of performance

The best way to explain this is through a case study. While most mining equipment has loggers generating data (and if your’s don’t then they should) the loggers on draglines produce the most comprehensive data.  A dragline with production and maintenance loggers will have over 2,000,000,000 signals processed into nearly 20,000,000 pieces of data, stored in databases every year for post processing.  (Is it any wonder that mines find themselves swamped by data? )

In this case study, the dragline is real and the results are real.  Most importantly, the lessons to be learnt can be applied to any operation and any piece of equipment.  This dragline historically operated at a production rate better than average.  When the maintenance logger was installed, a program of improving productivity and reducing damage was initiated.  The demand for change came from a range of areas, including, the workforce, technology, economics, competition,  etc.  The Mine Manager assumed the role of “change agent” and sought the support of a range of internal and external people who he perceived could help him.  Not unexpectedly, resistance to change came from individual and organisational sources.  In overcoming the resistance to change, the site focused on education, communication, participation, facilitation, support, and negotiation. 

A key part of this program was delving into the masses of data to provide specific and targeted reports to a range of people across the site.  Remember the word “meaningful”.  This is the key to operators and drivers understanding and changing their actions.  Data must be presented in a meaningful way. Reports included benchmarking, monthly production reports, operator comparisons, individual operator reports, and bucket reports, all of which included comprehensive productivity and maintenance information.  They included tables of data, line graphs, bar graphs, pie charts, and anything else the mine requested to help them understand what they were doing which impacted productivity or maintenance.  Of critical importance was the fact that these reports were followed up with visits from dragline “experts” and trainers who helped all levels on the mine site interpret the reports and develop plans for “change”.  In addition, all operators and supervisors attended off site courses which focused on team and individual understanding of the job they were doing.

The data was used to determine which digging techniques increased damage both from a global and an individual basis (comparisons were made both internally and externally).  Effort was made to identify which operators needed help with productivity or maintenance or both.  During the first 223 days of the program dig rate increased by 15% and boom stress decreased by 25%.  In conclusion, the data and the analysis of it were not the reason improvements were made.  Data was an integral part and improvements would not have been as significant without it.  However, the real impact was the organisational culture which was created. The dragline was changed into a “learning group” with the following characteristics;

·         A shared vision,

·         Old ideas were discarded,

·         The dragline operation was seen as a system of interrelationships,

·         People actually communicated with each other, and

·         Personal interest was less important than organisation interest.

Competitive Advantage for a mine or organisation comes from operating at a higher productivity and lower cost than others.  It should be seen as originating from doing a whole range of actions better than your competition.  On this definition, the dragline studied here has definitely assisted this mine in achieving competitive advantage.    The data was not the reason competitive advantage was gained but rather the most important strategic resource which itself was mined to extract the value.  Change was the mine's most valuable strategic ability and enabled the knowledge from the data to add value to the mine.

Graham Lumley  - CEO of GBI Mining Intelligence

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

Dragline Coach and Training Position Available at GBI.

Do you have dragline experience and looking for a better lifestyle?

·         Flexible work hours

·         Challenging and rewarding career

·         Reporting to HO in Brisbane,  though preferably located in Nth QLD

·         Wage – Generous Casual Daily Rate

·         Employer of Choice, with an excellent work/life balance

·         Work in an environment that embraces the values that have sustained the company since inception – Teamwork, Respect, Innovation and Ethics

GBI Mining Intelligence requires an experienced dragline operative to assist in the delivery of intelligent equipment performance data on mine sites throughout Australia.

GBI as the sole provider of intelligent mining information offers mine managers the unique means to achieve improved productivity and profitability.

Key elements:

·         GBI Mentoring Program

·         Operator Training & Development

·         Operator assessment

Technical Skills & Experience Required:

A minimum of ten years’ experience in the mining industry is preferred. The right person will exude excellent interpersonal and communication skills.
Previous experience in a senior role is also preferred.

Proven client relationship management and project delivery that meets client expectations will be highly regarded.

Working at GBI you will have exposure to a leading multi-national team as well as being a team-player.

For further information regarding this role please contact Lea Andlovec on 07 3147 8300 or email lea.andlovec@gbimining.com  

Please visit our website at www.gbimining.com

Please apply by 26^th Oct 2011. All applications are treated in the strictest of confidence.