The intersection between mining engineering and maximum production output

The intersection between mining engineering and maximum production output

By Motive Mungoni

Mining is an art of extracting mineral resources from the earth. From an investor’s point of view, it is a business venture which requires a huge capital base. Unfortunately, an investor’s return on investment is not guaranteed unless there is maximisation of production of a mineral resource. The quantity, quality, geometry and orientation of this resource has to be known and well-defined. Why? It is because one is dealing with a naturally occurring resource whose characteristics are pre-determined by nature and this carries a risk. The art is the part most critical because each mineral resource or ore body behaves and was formed uniquely and as such requires a distinctive mining approach. How to maximise production of the commercially viable part of the resource becomes the engineering component which determines the continuity of the project as a business.

In this context, engineering can be defined as the application of scientific principles and mathematical concepts in solving problems and designing ways that benefit the investor in their endeavour to make money. Accordingly, mining engineering becomes the use of maths and science to generate designs and solve problems within the mining arena. In other words, mining engineering is the one field which allows the miner to practically shake hands with the ore body.  It definitely does not involve magic, witchcraft or luck. It is a deliberate, predictive discipline that involves designing and planning at each stage of the mining cycle even to the detailed unit operations of the mine.

 Yes, of course, mining engineering doesn’t occur in isolation as there are other key fields linked to it such as geology and metallurgy. Regardless of its inter-disciplinary nature when it comes to production, it is the mining engineer’s main responsibility. It is his or her responsibility to make sure production targets are maximal. However, maximising output of a mineral commodity is no walk in the park. It then becomes a mining engineering problem of how to extract this mineral commodity and maximise its production sustainably. It is subsequently a maximisation production “problem”.

 In this paper, an attempt is made on how to solve this “problem” using best practices in mining engineering. A seven (7) Phase algorithm is proposed. However, to allow simple application, a generic view has been adopted. Examples of algorithms that have been used successfully in mining include network flow analysis, Lerchs-Grossmann 3D Graph theory, Linear Programming, Branch-and-Bound approach, Floating Stope just to mention a few. By doing so, the how and where mining engineering intersects with maximising production will be clear. The Phases in tackling maximal production are as follows:

Phase 1: Defining the problem and this has already been done- “To maximise production output

Phase 2: Observing and analysing the mineralised resource (ore body) to better understand its mineralogy; grade; depth from the earth’s surface; the physical and chemical properties of the targeted mineral.

Phase 3: Formulation of a mathematical model for the problem, that is, development of an algorithm with the parameters which one would have come up with in Phase 2.

Phase 4: Trial and/or testing of the algorithm to assess or evaluate its practical application. This makes use of the predictive performance matrix to ensure the algorithm developed is not only theoretical.

Phase 5: Develop an alternative algorithm or option B which the mining company can adopt in case option A fails.

Phase 6: Presentation of results to mine management and possibly investors to allow key decisions to be made in terms production targets; pay-back period; Net Present Value (NPV) etc. If there are any gaps, it may entail going back to phases 1, 2, 3 and 4 for more data collection, triangulation and verification.

Phase 7: Implementation and assessment of recommendations of the algorithm in sync with the mine management and investors’ vision of the mine company.

In a nutshell, the above seven (7) Phases are a brief but concise outline of the long and laborious envisaged stages in a mining cycle and in this case with the goal of maximising productivity. These Phases must be constantly monitored and updated dynamically as the environment changes to ensure the goal is constantly met. At this stage it must be pointed out that the design and planning of the mine by mining engineering excludes unit operations which some scholars ascribe to as the production cycle or extraction sequence. Also, in today’s world, the work of the mining engineer has been simplified because of mining software which use these algorithms on a daily basis. However, the mine planning and design still remains the foundation for the unit operations. Thus there is need to develop an extraction sequence and the stages in the development of the mine for it to maximise production. Important to note at this juncture is the mining method to be employed, vis a vis, surface or underground mining method. For conventional mining, a number of principal techniques have been developed over the years for mine production scheduling and these are but not limited to:

  1. Gershon’s heuristic- schedules extraction of blocks based on positional weight which reflects quality of ore in and position of block and quality of ore under block
  2. Parametric analysis- Derives series of nested pits by parameterising ultimate pit
  3. Stochastic optimisation- Attempts to find best path through deposit by generating a range of suitable solutions
  4. Maximum-metal pit sequencing- Derives series of nested pits for range of selected cut-off grades.
  5. Dynamic phase-bench sequencing- generates and evaluates all possible phase-bench combinations in search for sequence giving highest net present value

Interestingly, most of the techniques mentioned above are for the production scheduling of open pit mining operations. Description of these principal techniques have been expounded on by many scholars and literature on them is readily available. Very few techniques have been published for optimising underground mining operations. Furthermore, the techniques still have limitations which include:

  • Incapability of including benches and haul roads in the analysis of the ultimate pit concept for surface mining methods due to the static nature analysis of the deposit model.
  • On the critical issue of the cut-off grade, the assumption that it can only be optimised within the constraints of the suppled schedule is misleading.
  • Limitations on the option of blending of the different grades of the ore to minimise the effects of contaminants.
  • None of the current techniques are capable of allowing for the access requirements of the mine. This means that features such as haul roads, declines, and minimum equipment operating widths must be incorporated after the design and schedule have been produced.

Once the unit operations have been optimised, a mining company can be able to set production targets and can easily exceed them. This is possible because of the systematic application of mining engineering principles which are continuously improving and as a result low grade ore bodies which some years back were not economically viable are now being mined by pushing huge volumes, thus maximising production output. 


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