On the surface gaining access to equipment operating data seems simple enough. Prepare the mining truck with strain gages, accelerometers and other sensitive data collection instrumentation, record the forces as the truck is filled with dirt, rocks, gravel or coal and run the analysis to determine the results. While this might seem like a straightforward approach, the fact is that such short-term or controlled tests often bear little resemblance to what actually goes on when the camera isn’t rolling. For example, knowing they’re being observed, load operators might take extra care when filling the truck. While other times they might be less cautious crashing the bucket into the side of the truck bed, exceeding recommended load capacity, or dropping the load with greater force from a higher release point. At the same time equipment usage and its reaction to the environment can vary greatly depending on the operator, environmental conditions, location and any number of other factors.
While one can assume the normal operating conditions of virtually any piece of machinery, there are certainly occasions when equipment experiences an event outside of the range for which it was designed. For example, the drivetrain assembly of a fast-moving mining truck collides with a protruding boulder, an engine mount unexpectedly fails leading to excessive vibration, a front-end loader attempts a maneuver for which it was never intended, and so on. Observing performance over extended time periods in the system’s natural operating environment helps to ensure the likelihood of capturing the full range of conditions to which equipment is subjected – including rare but significant events. Armed with this information manufacturers can better quantify and predict future performance and develop products that satisfy the complete range of actual customer usage.