Recent advances in openpit strategic mine planning software enable the optimisation of intricate mining problems associated with a complex and vast array of parameters and constraints. These programs make use of mixed-integer linear programming to enable the simultaneous optimisation of the mining sequence, cut-off grade selection, mining equipment, resource levels, and capital expenditure to maximise the net present value of a project or deliver on other corporate goals.
Modern mine planning techniques at the strategic or life-of-mine planning level should be adopted by every company to ensure that mines are developed in the most profitable fashion within the bounds of practical mining.
At the strategic level, traditional mine planning involves following a series of sequential processes to evaluate the merits of different mine planning scenarios. Typically, a mine plan is produced based on fixed cut-off grades, and strives to achieve a primary goal, such as a target mill feed, while maintaining a smooth total material movement to simulate the operation of a pre-determined mining fleet. The mine plan is then used as a basis to calculate equipment hours and numbers. The latter form the input into cost models that calculate mining costs and overall project value. The process is repeated with different assumptions for total material movement, mine sequencing, or cut-off grades. Once the mining engineer developing the mine plan is satisfied that an adequate number of scenarios have been evaluated, the best outcome is selected and used for the rest of the process, such as waste dump and stockpile design.
The problem with a traditional approach is that the entire process can be time-consuming, sub-optimal from a value perspective, especially when the operation being planned is complex, and heavily reliant on the mining engineers’ understanding of the deposit and their experience.
The use of advanced mine planning software is becoming more and more widespread among mining companies and consultancies. Mixed-integer linear programming processes and advanced algorithms used in modern mine planning software allow rapid scheduling and evaluation of complex problems and help engineers and management make educated decisions regarding the best mine development strategy to adopt.
The power of advanced mine planning programs lies in their ability to achieve multiple targets while respecting a variety of constraints by “looking-ahead” to ensure that the choice of mine development made in Year 1 of production, for example, does not jeopardise its ability to achieve targets in subsequent years and achieve optimum value. This is a vast improvement from a traditional approach whereby a mine plan is derived one period at a time.
Improving a project’s NPV can be achieved by applying variable cut-off grades to each scheduling period. This is achieved by defining grade bins based on the spatial distribution of the ore and grade-tonnage curves. Advanced mine planning software can define a high-grade strategy that brings high-grade material to the processing facility earlier in the mine life while balancing the total material mined, and therefore the mining cost. Following a high-grade strategy may typically result in a 15% higher NPV compared to directly processing ore mined.
One of the issues with high-grade strategies is that mining additional material may require additional mining equipment. The impact of additional equipment on capital expenditure can be evaluated within the software by accounting for equipment hours as a variable in the model. Assigning a capital cost for additional mining equipment allows the software to gauge whether and when to increase production capacity to optimize the project’s NPV. Capital expenditure decisions are not limited to the mining equipment fleet and can extend to evaluating the merits and most suitable timing for increasing the process plant capacity or committing capital costs associated with developing a new pit (for example, relocating a village or building an access road).
Optimising project value becomes increasingly difficult for mining engineers when they are faced with having to satisfy multiple targets or constraints. In iron ore deposits for example, it is common to have to deal with stringent grade specifications and control of contaminant levels. Minimum and maximum grade constraints can be input into the advanced mine planning software to ensure that these constraints are respected over the life-of-mine while achieving planned production targets and optimising pit cutback sequencing to obtain the highest possible project value.
An optionality of these programs is their ability to simultaneously consider the constraints or variables mentioned earlier while optimising the location and development of waste dumps to maximise project value. Waste dump envelopes, representing the maximum possible waste storage capacity, can be imported into the software for evaluation. Cycle times from each mining block to each dumping block within multiple waste dumps are then used to generate hauling costs. The hauling cycle times and costs are then used to define the most suitable waste destination for each waste block to minimise hauling costs or level the hauling fleet over the project’s life.
Despite the advances in mine planning software, mining practicality still needs to play centrepiece to adopting the best development strategy. To avoid the “black box” solution that cannot be explained by the engineer, it is in the engineer’s best interest to produce multiple scenarios to demonstrate the incremental value generated and support the decision-making process.
This article covers only a few of the many applications benefiting from the use of modern mine planning software to maximise project value. However, it should highlight its potential as one of the tools that should be adopted by mining companies to ensure that the maximum value is extracted from their active mines or future projects.
Philippe Lebleu is principal mining engineer with international consulting firm, AMC Consultants
