Nchanga open pit fleet optimization for productivity improvement

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Date
2017
Authors
Dembetembe, Gift G.
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The University of Zambia
Abstract
Nchanga Open Pit (NOP) is facing a critical equipment planning decision after undertaking improvement projects at the processing plant namely Elevated Temperature Leaching, Heap Leaching and Cobalt/Copper separation. Elevated Temperature Leaching has resulted in 20% increase in the recovery of copper while cobalt/copper separation is anticipated to bring 77.5% increase in the value of the final product. The improvements at the processing plant have subsequently led to extension of life of mine to 4 years. As a result of the above, all upstream components of the value chain have to be harmonized with these improvements in order to maintain productivity at optimum level and curb loss of value. Currently, NOP is faced with a critical equipment planning decision where the current ore handling fleet has to be either re-capitalized or apportioned to exploit new mining areas. Therefore this study was undertaken in order to optimize the fleet in terms of both size and performance. In order to achieve the stated objective, production planning, fleet optimization and fleet management were reviewed and analyzed based on generic formulas, match factor theory, Overall Equipment Effectiveness (OEE) and queuing theory while analysis of fleet performance and simulation was done by using Talpac software. Results of study indicated that NOP needs to invest in machinery by either re-capitalizing the current fleet or resorting to a more cost effective fleet management approach. Fleet optimization at NOP had six interacting factors which have attributed to low fleet performance. These factors are low machine availability, low machine utilization, mismatch between loaders and truck fleet sizes, double handling of ore, costly dust suppression system and flawed maintenance system. Furthermore, based on fleet deterioration, assessment of fleet performance using OEE showed low Overall Equipment Effectiveness of 7.2% for shovels, 13.6% for large excavators and 17.6% for trucks against a score of 85%. The study has also established that the number of trucks needs to be increased from 15 to 28 if the current haulage system has to be maintained or alternatively use the conveyor belt system. However, to do this, a reliability and maintainability analysis has to be done which is beyond the scope of this study.
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Mining engineering
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