Simulation of Truck-Shovel Operations Using Simio

Short Communication

Authors

  • Ibrahim Amin
  • Muhammad Adil Department of Mining Engineering, University of Engineering & Technology, Peshawar, Pakistan
  • Safi Ur Rehman Department of Mining Engineering, Karakoram International University, Pakistan
  • Ishaq Ahmad Department of Mining Engineering, University of Engineering & Technology, Peshawar, Pakistan

DOI:

https://doi.org/10.46660/ijeeg.v8i4.734

Abstract

This research work was mainly directed towards the selection of optimal fleet for a cement quarry using 3D
simulation models with Simio, which is the most convincing and understandable tool for quarry managers and staff.
Quarry, haul roads and their specifications were taken from Google Earth while fleet capacities, and cycle time of
operations was assumed matching with realistic data of a cement quarry. The objective of this study was to provide
feed for two crushers of 300 tph capacities with minimum number of trucks and shovels. Student (academic) version of
Simio software was used. Scenarios of quarry were created by exporting quarry data of Cherat Cement Ltd., from
Google Earth in Simio. Total seven scenarios were checked by changing number and capacities of trucks and shovels.
The model yields different results for various situations. The best results were selected. The model presented can also
be used for deciding best location of shovels on different faces depending upon the chemical composition of materials
available at faces for making ideal feed for kilns. The management could rightly decide by using the simulation models
for complex processes at mining/quarry operations and could easily generate report and visual presentations.

Keywords: Optimization, simulation, cement quarry, Simio.

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Published

2017-12-30

How to Cite

Ibrahim Amin, Muhammad Adil, Safi Ur Rehman, & Ishaq Ahmad. (2017). Simulation of Truck-Shovel Operations Using Simio : Short Communication . International Journal of Economic and Environmental Geology, 8(4), 55–58. https://doi.org/10.46660/ijeeg.v8i4.734

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