Stochastic modelling of Continuous Miner based underground coal mine production planning through curve-fitting and regression approach

coal mining are continuous miners (CM), shortwalls, and longwalls.
According to the relevant literature, the available studies have not
been able to successfully link the productivity of CM-based systems
to the related independent parameters. However, this study makes
an effort to find correlations between a number of independent
variables and production-related attributes using regression
modelling and curve fitting. A combined relationship was
constructed considering all independent parameters as input and
production-related parameter as output, and a relationship was made
considering each input parameter separately with the productionrelated parameter as output. The idea of their strong association to
represent the interrelationship conveyed by their statistical goodness
of fit (R2
and RMSE) and the results of the t-test further support
their relevance. The greatest R2 value was shown for seam thickness
(0.8779), followed by pillar area (0.84), gradient (0.8112), and coal
strength (0.6008). Besides geo-mining input parameters, the cutter
motor power has shown a better correlation with production-related
parameter, with its corresponding R2 values of 0.8033. The
pertinent data from three CM panels (not considered during
equations generation) were then incorporated into the derived
interrelationships. These validation results were then compared
using a t-test to the equivalent actual field data, which revealed a
minor discrepancy. The interrelationships were found to be
applicable and pertinent in CM–based underground coal mining
situations.