Abstract:
The current coal mining climate is characterized by coal price volatility,
political instability, high labour costs, and increasing operational costs. This
is exacerbated by a steady decline in the growth of global coal demand due
to the increased use of alternative and renewable fuels in the energy
industry. Locally, the overall mining cost inflation indices shows a yearly
increase of 2% over the national consumer inflation. In order for coal mines
to survive and mine profitably, they need to capitalize on the opportunity to
improve their productivity and focus on one factor they can control:
operational efficiency. Increasing productivity is one of the key drivers to
counter diminishing profit margins. Increasing production effectively
reduces operating costs. However, the emphasis should not only be on
increasing output with the same input, but increasing the output while
decreasing the input, and ultimately adding optimum value to current
resources. Research shows that an increase in production will ultimately
decrease the operation’s unit cost, especially fixed costs.
In this study a load-and-haul fleet optimization approach has been used
to identify the opportunities for operational improvement at an opencast
colliery. The study combines the results of a literature review, on-site time
studies, and statistical data analysis in order to determine the best loadertruck
fleet combinations for increased production. Several relevant key
performance indicators (KPIs) for the evaluation and identification of
productivity improvement opportunities were defined during this study.
These KPIs are bucket fill factor, loading conditions, loading cycle time,
utilization, and deviations from schedule. The priority delays determined by
on-site time studies compared to the time book for each delay showed that
idle or waiting time by the loaders, face preparation and relocation, and
process delays had significant deviations. However, the results showed that
this operation is under-trucked, hence optimizing the loader-related inputs proved less effective than optimizing truck-related inputs. The results
indicated that a homogeneous truck fleet consisting of five Caterpillar 789C
trucks, combined with a Caterpillar 994K loader, is the most efficient fleet
option and will produce 1455 t/h. The combined optimized effect of each
identified KPI of production led to a tonnage improvement opportunity of
5421 t per shift.
