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In recent times, the use of advanced
mathematical and computer science skills required by mining engineers have been under attack. The tremendous steps in
computer technology brought new dimensions to mineral training. Should university training programs be drastically
modified to accommodate demand of computer science oriented mining engineers or should mineral curriculums be condensed
into smaller units each with specialty fields of practice to satisfy industry needs.
Mathematics and computer science competence has
become crucial in order to satisfy constant mining technical
challenges faced by mining engineers. These challenges may exist in the areas of actual mineral extraction
or the managing of labor costs or other domain of the industry always with an increased focus on sustainable mine
life operation outlook.
Mineral activity in years past did not heavily include the use of computers in the mining process. Mining
was different in some ways where, say, practical knowledge on the use of percussion drilling and explosives in
tunneling was critical. The introduction of tunneling big-rig hardware and other equally high performance mining
equipment, changed the landscape slightly in which mastering knowledge in fields of rock mechanics, applied mathematics
and fluid mechanics became more critical.
The mineral industry has routinely increased
the use of sophisticated numerical algorithms to derive suitable
production day-to-day schedules in complex mineral operations, where the direction is pointed at utilizing larger
and more complicated mathematical models. There is also a heightened industry focus on numerical models and other
efficient methods for numerical treatment of control problems whenever these arise in the decision-making process.
In this framework, optimizing mineral
extraction and decision-making are challenging and interesting . Fortunately,
there are many mathematical algorithm models to help along the way. For example, if dealing with statistics analysis
based on experimental observations, a variety of techniques like Fisher-Snedecor or Least-Square Fit distributions
and other regression methods are widely applied. When confronted with specific rock mechanics intricacies methods
following Runge-Kutta theory may provide adequate solutions. As a general rule , specialty areas of function evaluation,
interpolation, iterative algorithms, series, linear algebra, statistical analysis, optimization, linear and nonlinear systems
are heavily used in mining applications.
For mining to develop and apply such
complicated, multidimensional models necessitates, however, a well-trained and
experienced staff with expert knowledge of numerical analysis techniques, computational procedures and mining itself.
Today, strong indications substantiate that people of this profile are not too frequent in the mining industry.
It is quite evident that complex computer
mathematical algorithms do indeed provide the tools for methodological progress
and are most welcome and helpful in improving the mining engineer's problem-solving capacity. They are the right tools
and equally important is the task of equipping computing know-how into the mining engineer’s toolbox.
Practical samples and further interesting
discussions on mineral engineering can be found at http://www.keystoneminingpost.com
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