How many Laser drivers expect to reach the top speed of an SS Commodore. Alternatively, how many SS Commodore drivers expect their fuel economy to match that of the small car? The reasons drivers don’t hold these expectations is that they realise that their vehicles have special qualities. That doesn’t mean that they can’t learn from each other — the Laser driver may be able to improve top speed by using high octane fuel and getting the engine tuned regularly (as the SS owner does), while the SS driver could learn about less aggressive city driving to reduce fuel consumption.
In each case performance will improve. So what does this have to do with coal mining?
For years, Australian longwall mines have aspired to the productivity levels achieved by their US counterparts. Australian workers have visited US operations, and some mines have employed American people to manage day to day operations. Industry averages have been compared and the headline grabbing operations have been held up as examples of what can be achieved. Just about every mine and head office will have their own version of Figure 1 using measures such as total production or productivity, to show how much better the US mines are.
Mines have been built, capital has been justified, and employment numbers set using these figures, only to see actual performance fall short of that expected. Numerous articles and papers have been written trying to define that “magic component” that is so different. These figures have led to much hand wringing and gnashing of teeth as Australian mines keep searching for the secrets that will make their performance jump from the blue line onto the red line in these mesmerising graphs.
But for a longwall mine trying to improve performance, are these comparisons really meaningful? Should mine A with a trunk belt system rated at 2000 tonnes per hour compare total production with mine B that has a system rated at 5000tph? Should the productivity of mine C which needs gas drainage be compared to that of mine D which doesn’t?
The answer in each case is yes, but at a detailed level. The comparison needs to go beyond the headline figures, to a level of commonality, to identify improvement opportunities.
Taking a simple example, two mines (let’s call them E and F) have the same number of employees and produce the same output each year. Both mines have the same longwall equipment (a package deal from the manufacturer), yet E averages a cutting rate 10% higher than F. Can F improve by learning about E’s cutting method? Could E learn about time management and production scheduling from F? Was the headline comparison really worthwhile (same output, same productivity)?
The low hanging fruit has already been picked off the performance improvement tree, and lower branches must be cleared away if more fruit is to be found. The best way to “clear away the branches” is to gain a thorough understanding of your own mine’s management and operational practices, getting back to first principles to show what activities impact on each other, and identify constraints. Only when this is fully understood do comparisons become meaningful. Looking beyond the headline figures of tonnes produced and tonnes per man year, other key performance indicators (both input and output) can be used to measure performance and highlight areas of potential improvement.
Driver tree analysis, as shown in Figure 2, allows comparison of equivalent measures, and investigation of areas with substantial differences. While there may be no fruit on one branch of the tree, the other branches are not necessarily barren. The people branch may show the benefits of hot seat changes, while the equipment branch will reflect maintenance programs and equipment age. In any case, even though the headline figures may not be achieved, the driver tree analysis will show areas with scope for improvement in your mine’s performance.
So what about the US mines? Different equipment, different legislation, different industrial relations and different conditions are all issues used to justify not going to the next level. Normalising and reviewing at the next level down allows true comparison of performance and effectiveness. Provided the differences are acknowledged and factored in (or out as the case may be), all levels of activity from the root cause of delays through to whole of mine production can be validly compared.
As an example, Mine USA has a longwall rated at 5000tph. Annual production of six million tonnes is equivalent to 1200 run hours at full capacity. So if your mine’s longwall is only rated at 2000tph, what total output would you consider to be equivalent to Mine USA’s performance?
Clearly differences in equipment capacity can be easily accounted for, but what about conditions? While it may be true that on average, mining conditions in Australian mines are similar to those in America, is this the case for the benchmark mines? Do they deal with seam gas and spontaneous combustion, are primary support requirements similar, and do they have the periodic weighting events that several Australian mines experience?
The headline mines in the US are located in the western parts of Pennsylvania, and in Colorado. An interesting NIOSH article (Roof and rib fall incidents and statistics: a recent profile) shows that on average, all longwalls in the US have 0.89 roof fall events per 200,000 employee hours. However, in the longwall mines of western Pennsylvania, the average is only 0.56 roof fall events per 200,000 hours, while the average for western US longwalls (covering Colorado, Wyoming and Utah) is 0.41. The Pittsburgh No.8 seam, which is widely mined throughout Pennsylvania and West Virginia, is virtually gas free as are many of the seams mined in the western states. Spontaneous combustion is an issue at several western mines (as shown by recent events), but some mines in Pennsylvania actually ventilate through the goaf!
