My Job When I was 22: explained
Written in early 2021.
Mining Engineers and engineers more broadly, often spend time optimising a solution to a problem. Optimisation can be defined as the process of finding the best design or solution. In practice, optimisation does not exist in a vacuum. Limitations on the process, likely time and money, constrain how optimal a solution can feasibly be. The aim of this article is to highlight the importance of optimisation but also to consider the inputs and process leading up to optimisation.
Most problems solved by engineers will be optimised implicitly and not necessarily consciously. They use their wisdom, knowledge and general judgement when solving a problem leading to some optimsiation.
There are some problems, however, that even the most hardened, wise and smart engineer is not able to solve unassisted, let alone optimally. Generally these are problems where the optimised solution must take into account a large number of interconnected variables and constraints. In mining, these sorts of problems often present themselves when in the medium to long term planning space.
It is worth considering why we use optimisation tools. Primarily, in mining, optimisation is used to increase the value of a project and make more money. Optimisation often presents itself as reducing the time it takes for a process to complete. A crude example: when planning a mine, based on optimisation, it is suggested that the mine buys extra trucks at cost (CAPEX & OPEX) to move more ore per unit time. This generates more revenue sooner. The planning optimisation has deemed that the net benefit to the NPV of purchasing the trucks outweighs the required CAPEX..
In long term mine planning, optimisation tools can be used to find solutions to problems which have too many variables and constraints for the human mind to process alone. To continue with the above example, there is the possibility of a plant upgrade for some extra CAPEX allowing the processing of more ore per unit time. The optimal solution must weigh up both the cost of the trucks and plant against the extra revenue both or either may bring by changing the rate of ore processing per unit time. It is also possible that neither is optimal - their extra revenue does not outweigh their costs. The problem, with only two added dimensions, has become much harder to solve. In this situation, good mine planning software with the appropriate inputs would find the optimal solution which is the most valuable solution. This is a glimpse into the work I’ve been learning about and carrying out while strategically planning mines at IMC Mining in Brisbane, Australia. It has made me actively consider what “optimisation” means.
There are three points to consider; firstly you need accurate and relevant inputs. In the above example this would be ensuring that the quotes for CAPEX and OPEX are up to date and reliable as well as ensuring that the extra ore tonnes are represented in the block model accurately. Secondly, if the process of optimising a solution takes too long or is increasingly complicated, is the process of optimisation actually wasting time and resource? Will the generation of inputs be easily understood by colleagues or documentable? Finally, consider what goes on behind a button which optimises. As the engineer pressing the button, are you confident in understanding the results it produces?
I want to stress that this theory can be applied to all levels of optimisation from long term strategic mine planning using linear programming to using Excel's “Goal Seek” for choosing a better loader matched to a truck fleet.
I spend a lot of time considering optimisation and the process leading to an optimised solution. I think that the best engineers must always think about using the best optimisation tools. The problems that can be optimised are not necessarily complex. Reducing the time required for an engineer to complete any task can increase profits. But it is important to think about the whole process - input data, optimisation input generation and the process itself all need to be weighed up carefully.