Road maintenance management
&
optimisation

Haul roads at surface mining operations are often not systematically maintained and as a result, cost- effective road maintenance is poorly defined.

A haul road maintenance management system utilises a total road-user cost approach in identifying the optimal frequency of road maintenance.

Rolling resistance assessments combined with mine haul truck operating cost models are used to show how the optimal frequency of road maintenance can be determined.

A typical application is presented which illustrates the potential of the technique to manage maintenance as and where needed with resultant reduction in total road user costs and an improvement in service provided for the road user.

A task many surface mine operators face is how to justify expenditure on a haul road, either as a new construction or a roads campaign (rebuild or improvement of an existing road).

The value-proposition for investment in road improvements needs to be justified in the context of the total cost of material haulage.

The relationship between truck speed, rimpull and gradeability is used as a basis for models that enable the impact of poor road conditions on truck cycle time and fuel burn to be assessed.

These relationships are then used to build a haulage cost model, applicable to both conventional and autonomous haulage systems, from which a ranking is derived identifying segments of the road network from which the benefit the most from an improvement campaign.

For the majority of operations, fleet management systems record truck metrics including the truck response to the road it runs on. In truck haulage, cycle times can vary as a result of many factors, not the least of which is the road condition itself. Whilst we may see, over time, an increase in cycles times, it’s often harder to explain the source of that increase – especially if and when it is related to road deterioration as opposed to simply the geometrics of the haul itself.

One critical measure of truck performance is based the impact of increased rolling resistance on cycle times and unit costs. But can a measure of this effect be extracted directly from existing ‘big data’ and used to inform road management strategies?

Ultimately, it may not be just as simple as ‘today’s rolling resistance is 3%’, but rather interrogating the data to reveal an incremental change indicator which would flag a more pro-active response to road maintenance, as opposed to the reactive responses more typical of current operational strategies.

Real-time road performance monitoring systems offer the mine site valuable insights into the conditions across their network of roads. Many options exist tailored to the specific site, operational and infrastructure requirements..
Ideally, multiple levels of information should be accessible to fully interrogate a road defect when identified - truck response, visual information, mapping etc.With any of these systems, a key factor to consider is how the information is processed, delivered, prioritized and integrated into the sites WMS. Without a full integration across management systems, the value of the data wont be fully leveraged to generate improvements to haul road and haulage system performance.Additional considerations relate to how the 'fix' is applied. It is important to understand the root cause of the identified under-performance in order to apply the correct remediation. Is it geometric, structural or functional? Using the resources on this site will help you focus on the real underlying causes of your road's poor performance.Data management & road monitoring system examples shown here (a few of many options) are sourced from