Monitoring of tires for surface mining operations has come down to a single focus - how can I make my tires last longer? The immediate response may seem quite simple, but the implementation of remedial measures still does not entirely meet the expected outcome. We all know that running a tire for too long a period causes heat and mechanical separation issues, and that inadequate running surface housekeeping can lead to cuts and other damage. Despite much improved attention to these areas, we may still be missing an opportunity in terms of how we measure tire life with operating metrics to identify damage concerns. The tonne-kilometre per hour (tkph) measure is taken as an indication of tire life in terms of loads moved over a certain distance within a given time frame. Monitoring and reporting of such values are commonly taken as an average for a given shift, week, or month, and through the averaging process, we may be missing critical information. Why should it be, for example, that two similar trucks operating on similarly maintained ground surfaces have tires on one unit that greatly outlive those on another?
The picture becomes clearer when we consider the individual tire motion relative to the ground surface on a real-time basis. Within any given duty cycle, from loading device to dump locale, the ground surface may be free from debris but will develop a rolling profile, albeit slight, due to long-term surface deformations from extended use. As the tire moves across the surface, it will react to the ground profile through response at the suspension. As a result, a given tire may, from time to time, float over the ground surface at the expense of transferring the load to the other tires on the unit, or it may itself impact the ground with a greater single load.
If we consider that all tires on a truck under stationary conditions are subjected to the weight of the truck or effectively what we refer to as a “1g” load, then depending on the motion of the truck and the nature of the running surface profile, any tire may be subjected to loads less than or greater than 1g, depending on the dynamic motion of the truck. In fact, under some adverse ground profile conditions where a truck was subjected to excessive rolling, pitching, and twisting (racking) motions, the load level on a given tire was measured as high as 4g, that is four times the nominal load expected to be carried by that tire. However, on review of the average tkph data for the shift, the occurrence was not apparent.
The previous situation is a concern. Consider that if a large number of repetitive loading cycles are imposed on a structure, it will eventually fail. If the load level is increased and the same number of cycles are imposed, then the structure will fail sooner. If we measure the average load for the given duration of service, the peak event evidence becomes smoothed out. It is still there but we do not recognize its presence and impact. So what is the answer? How do we monitor this phenomenon and, more importantly, what can we do about it? Using an alternative approach for measuring a tkph equivalent that accounts for the frequency and size of peak loading events would be a good start. Software, such as that displayed in the diagram, allows snapshots of strut loading expressed in “g” level, which then captures the tire peak loading events.
With the capability to then measure tire loading as a truck operates on a given haul road, the truck becomes an indicator of haul road conditions. Data is already being collected for most trucks; we just need to be able to transform the information into a measure that more effectively indicates haul road condition. A truck equipped with this measurement and reporting capability provides the necessary feedback for operations to more effectively dispatch grading equipment to profile haul roads and lessen detrimental dynamic loads on tires. Innovative reporting of what the truck can tell us, about not only its own performance but that of its tires and the running surface below, allows us to take action and improve tire life.
Gord Winkel is technology manager, Kearl Oilsands Project, and Tim Joseph is president and principal engineer, JPi International Ltd. and director AEGIS, University of Alberta.