Specialist mining advisory company Ukwazi Mining Studies was selected to assist a major mining client with the streamlining and automation of its planning process for a sizeable Southern Africa openpit coal operation last year.
“The client had many challenges ranging from inconsistent data and misaligned processes to duplicated information within the planning operation, all of which Ukwazi improved,” says Ukwazi senior mine planner Branden Paine.
He points out that one means of instilling opencast efficiency is for experienced technical specialists to have a technically sound execution plan, prepared in collaboration with a competent execution team.
This allows for a scenario where “a client can plan what to mine and mine what is planned”, provided that there is operational transparency, as well as cost effective and safe execution of the aforementioned plan.
Within this type of planning scenario, the solutions proposed must improve turnaround time and accuracy of the planning function, through using existing software, and enhancing its functionality to cater for the required improvements.
Although every operation’s process is unique, there is often room for improvement through standardisation, customisation and automation of mine planning processes to deliver improved operational and financial performance per pit or operation, Paine adds.
He suggests that operations’ compliance to plans is generally low, owing to a range of factors, including misalignment between the imperatives of management and the owners, as well as contractor performance.
Low compliance can also be attributed to the selection of inappropriate fleet options, such as the client using the wrong tools for the job, which causes low productivity and high maintenance costs and/or frequent breakdowns.
There can also be a disconnect between the contractors if, for example, one is responsible for drilling and blasting, and the other for mining.
Paine warns that the danger, however, lies in operations adopting a ‘command and control’ approach – trying to force a standardised process to replace its existing process without a full understanding of such processes.
Further, technical and operational staff may manually circumvent the plan when required to produce results in continuously tightening timeframes, owing to software limitations and/or knowledge shortfalls.
Having appropriately qualified mine planners and mining engineers is always a challenge. “There are nuances to mine planning that develop over time, based on a blend of the theoretical and the practical,” maintains Paine.
While Ukwazi does engage in providing some mine planning training, the company notes that it has found that placing its engineers or planners on site with the client to support the planning and operational improvement processes is far more effective.
“The support provided is the basis of continuous and incremental improvement of the future of the planning function, demonstrating the need and movement towards customised and automated planning software solutions,” says Paine.
Moving away from manual systems has assisted operations in transparently monitoring performance and compliance while identifying risks earlier, thereby ensuring a proactive rather than reactive environment, which is essential to its purpose for all stakeholders.
Meanwhile, Ukwazi has taken a page from its own book to mitigate the current challenges that the industry and the mining sector faces because of the Covid-19 lockdown.
“Our response has been to ensure that all our technical staff and project teams are able to work remotely and are placed in a position where they can continue to deliver quality services to clients,” stresses Paine.
However, he adds that, although some of its staff and functions can be managed remotely, actual operations cannot be executed remotely, which is where mining differs from other industries.
Paine does suggest that the industry has shown it can be agile, flexible and resilient, and should recover in due course.
Ukwazi’s view is that the future of planning will be based on customised automated solutions using machine learning to optimise planning processes and identify risks proactively.
“Mine planning will become more and more reliant on automated dataflow through integrated systems, which enables the operation to streamline and monitor critical tasks based on real-time, valid data,” concludes Paine.