Production Performance Evaluation of the Hoisting Systems at an Underground Gold Mine

The production performance of two hoisting systems operating in series at an underground gold mine was evaluated based on several key performance indicators (KPIs). All the KPIs were lower than the mining industry benchmarks, mainly due to lengthy and recurrent machine downtimes. Frequent breakdowns, power cuts, poor maintainability, and shaft flooding were some of the factors affecting the overall performance of these systems, as captured on the developed Fishbone Diagram. The average cycle times were much longer than expected, and the production rates were significantly lower at a 5% significance level than the requisite 160 tonnes per day. There were mismatches in the throughputs of the hoisting systems, indicating an unbalanced hauling process. Therefore, the current maintenance strategy for the hoisting systems warrants review in order to cut downtime. Alternative power sources are needed to complement electricity from the national power grid. The methods, findings, and data analysis techniques applied in this study can be used for evaluating the performance of mining equipment elsewhere, benchmarking and optimisation functions.

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Publication Details

Journal
Archives of Mining Sciences
Published
2025-03-28
DOI
https://doi.org/10.24425/ams.2025.154161
Primary Topic
Mining Techniques and Economics
Type
article
Field-Weighted Citation Impact
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article

Production Performance Evaluation of the Hoisting Systems at an Underground Gold Mine

Melvin M. Mashingaidze, Pitchou Mukendi Bukasa, Richard T. Mupeti
Archives of Mining Sciences
Mining Techniques and Economics
article

Production Performance Evaluation of the Hoisting Systems at an Underground Gold Mine

Melvin M. Mashingaidze, Pitchou Mukendi Bukasa, Richard T. Mupeti
article en

Abstract

The production performance of two hoisting systems operating in series at an underground gold mine was evaluated based on several key performance indicators (KPIs). All the KPIs were lower than the mining industry benchmarks, mainly due to lengthy and recurrent machine downtimes. Frequent breakdowns, power cuts, poor maintainability, and shaft flooding were some of the factors affecting the overall performance of these systems, as captured on the developed Fishbone Diagram. The average cycle times were much longer than expected, and the production rates were significantly lower at a 5% significance level than the requisite 160 tonnes per day. There were mismatches in the throughputs of the hoisting systems, indicating an unbalanced hauling process. Therefore, the current maintenance strategy for the hoisting systems warrants review in order to cut downtime. Alternative power sources are needed to complement electricity from the national power grid. The methods, findings, and data analysis techniques applied in this study can be used for evaluating the performance of mining equipment elsewhere, benchmarking and optimisation functions.

Archives of Mining Sciences
University of Namibia (NA)
Openalex Percentile: Top 94%
Mining Techniques and Economics
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