Effect of Ignoring Input Correlation on Truck-Shovel Simulation

Abstract

This paper presents an approach for handling correlated input variables in discrete event simulation (DES) modelling of truck—shovel systems using commercial DES software and uses a case study to investigate the effect of ignoring correlation between input variables. Multivariate random vectors, instead of independent probability distributions, are used for variables found to be correlated. The authors prove that correlations do exist in truck—shovel haulage systems. The model with multivariate random vectors performs better than the original model. The significance of modelling correlation in input variables depends on the strength of the correlation and the output's sensitivity to the input variables.

Department(s)

Mining Engineering

Keywords and Phrases

Commercial vehicles; Computer software; Correlation methods; Probability distributions; Shovels; Trucks; Haulage system; Input correlation; Input variables; Original model; Random vectors; Discrete event simulation; Correlation; Multivariate analysis; Numerical model; Software; Vector; Correlation; Multivariate random vectors; Shovel-truck simulation

International Standard Serial Number (ISSN)

1748-0930; 1748-0949

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2016 Taylor & Francis, All rights reserved.

Publication Date

01 Sep 2016

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