Statistical Analysis of Loading for the Simulation of Belt Conveyor–Based Transportation System

Mean inter–arrival time of haul trucks at the loading points was calculated from the arrival count recorded in a time window of 15 min from five consecutive working days, each of which divided by four shifts. Normality of all distributions was investigated with D’Agostino–K², Anderson–Darling and Kolmogorov–Smirnov normality tests. Courses of most haul trucks of class A gave right–skewed, leptokurtic distributions, while of class B and C slightly left skewed, platycurtic distributions. The obtained values of mean inter–arrival times were almost identical for haul trucks of class A for the loading points located within the G–1 and G–4 mining departments. Haul trucks of class B and C yielded similar bimodal–like distributions, which for G–9 department showed more left–skewed triangular–like distribution pattern. Most of the haul truck courses did not exhibit normality of distribution of mean inter–arrival times, thus the non–parametric Spearman Rank and Kendall correlation coefficients were calculated. Only the haul trucks of class A represented significant Spearman rank correlation at the 0.05 level for G–1 and G–4 mining departments. Thus, the histograms of the haul truck courses will be taken as empirical distributions from which the haul truck courses will be modelled in the FlexSim simulation of the mine’s transport system. The data shown that mean inter–arrival times of the haul truck courses did not differ significantly among various parts of the mine and are more haul truck class–dependent. Typical values of mean inter–arrival times were in the ranges 400–500 s. Maximum inter–arrival time corresponding to distance limit for the mine was 900 s. Haul trucks with the largest shovel capacity were sent to such mining fronts. LHD’s with lower shovel capacity were used where several mining fronts were exploited in the same time by several haul trucks.