The Situation
The current operation has several areas where the fleet is not productive. Some of these are inevitable, such as the maintenance of the fleet or driver-related events, including breaks and shift changes. Others are potentially avoidable, such as waiting time and queuing time, and the existing computer controlled dispatch system did not address these.
Our Approach
We modelled the operation of the mine using Opturion’s Dynamic Transport Optimiser. In particular, we used some features of the product that were perfected and stress-tested in large-scale transport optimisation projects in the forestry industry, notably the modelling of excavator operations. We decided to optimise the entire month’s operation in a single scenario, which consisted of scheduling tens of thousands of individual loads.
Opportunities
In-mine transport consists of transporting full truckloads from excavators to dumping locations. Sometimes there may be the choice of where to dump a particular load, but often (and in this case), that choice is fixed beforehand, and the number of loaded KMs are fixed accordingly. There are some remaining opportunities at the tactical planning level (day ahead/start of day) then:
- Minimising empty KMs
- Minimising waiting time (queuing) at loading and unloading points
- Optimally scheduling driver breaks and shift changes as well as maintenance, in particular, to make use of otherwise wasted time
Unexpected Outages
Furthermore, on the day, there is the opportunity to reschedule around unexpected outages and other disruptions. For instance, if an excavator breaks down unexpectedly, we may quickly divert vehicles elsewhere. A manual planning process often struggles to cope with such situations.
Finally, the positioning and availability of excavators are essential factors in achieving operational efficiency. Limited availability may lead to vehicle queuing problems, and excavators should move in sync with a dynamically evolving transport plan, e.g. moving to the following location as soon as work is done.
The Results
For this particular operation, we estimated that the benefits of optimisation in minimising queuing and waiting for the trucks, with no changes to excavator deployment, would exceed 15%.
We estimated a further 10% efficiency gain by optimally deploying excavators in line with the (dynamic) transport plan.
