Current technological advancements, that allow real-time monitoring of mobile mining equipment parameters, are able to add a new dimension to the way we manage the operation and maintenance of assets. Bluefield has been helping clients for some time to understand and realise the capability of their site data analytics systems by combining technical equipment knowledge, practical maintenance experience with an analytical approach. There are many systems available but only by combining with good practical knowledge of equipment and maintenance, can these systems deliver their promised benefits.
The ability to baseline the fleet operating parameters allows exceptions to be identified and investigated long before they have the ability to progress to failure and impact operations. This not only allows the unit to be stopped somewhere safe or directed to the workshop in a scheduled manner but can also limit the associated cost of major component damage.
Some simple examples of what we have encountered include:
Monitoring the relationship between fuel settings, boost and engine load to identify units with performance issues. These issues can have a significant effect on fuel cost, cycle time, queue time and speed on grade etc. Rectifying these exceptions can then add to the efficiency of the operation through increased production and reduced operating cost as well as ensuring the engine is working to design.
We have identified high fuel burn instances, caused by a simple rise in the haul road profile, these have made visible fuel burn increases of 5-10 liters for a couple of minutes. When multiplied by a fleet of trucks over an extended period of time that little bump has a significant quantifiable fuel cost associated with it.
Additionally, the analytics systems can be used to optimise the ground maintenance diagnostics and minimise the diagnostics time.
Consider equipment that overheats, where do you start? How long does that investigation take before you zero down to the actual cause? How much time and money is spent diagnosing before the fault is found? It is simple to use the analytics system to identify, for example, the source of excess engine heat generation, such as in one engine the #12 cylinder exhaust temp was 100°C hotter than every other cylinder. This enabled the maintainer to go directly to the fault and identify the cause, saving many man hours and equipment downtime hours, trying to identify where the fault was.
While these are just a few simple examples of what we have found, the opportunities are endless. In our experience, the key is to understand in detail all of the machine parameters and link the exceptions with the equipment failure modes, which requires a closed-loop communication between the analyst and the maintainers on the ground.