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Electric Rope Shovel Operation Enhancements, Understanding and Modelling the Impact of The Operator
- Author / Creator
- Yaghini, Ali
The loading and haulage system is considered a prominent part of a surface mine operation. Improving the system enhances the productivity and economics of an operation to a great extent. Operators play a critical role in the mine overall performance and production. Autonomous truck fleets have been utilized and proven to be effective in mitigating the influence of operators’ and improve mine production. However, there is limited work that focusses on the influence of shovel operators on mine production nor on the potential benefits of autonomous or semi-autonomous shovels.
This thesis uses detailed data available from a shovel health and payload monitoring system to study the important role of an operator in the shovel and mine production and performance. It introduces a metric that captures operators’ efficiency, identify opportunities for improvement, and last but not least, proposes a methodology to study the extent to which any proposed improvement including automation could enhance the shovel, truck and mine operation.
Based on the knowledge gained from performing a statistical analysis on a shovel operation database, the “Operator Relative Score” (ORS) is developed. Dig, swing and return times, bucket load and number of passes to load a truck are identified as critical tasks with variations among operators. The ORS is implemented in a case study that led to identify best and worst productive rope shovel operators. To further study the nature and influence of variations among operator practices on overall production, a discrete event simulation submodule is developed that includes operator behavior and this is integrated into a surface mine operation discrete event simulation model. Results showed that an electric rope shove operator could affect shovel production, number of trucks, and queue times by up to 20, 16, and 41%, respectively.
To mitigate the influence of operators on production two techniques are introduced. “Dynamic Target Loading” (DTL) as a tool to provide an operator with the flexibility needed to reduce loading time and compensate for situations where trucks are waiting at loading queue. Its potential to improve the overall mine production is evaluated using the developed discrete event simulation model. Results confirmed that in addition to lower wait time and number of trucks in queue, the overall shovel production can be increased by 12.1%.
The second measure introduced in this research is “Projected Hourly Production” (PHP). This KPI respects the 10:10:20 rule, combines loaded truck final load ratio with the loading cycle time and compares the result with the best recorded practice. The result provides the operator with tangible feedback on their loading strategies and can help them optimize their tactics. It is envisioned that by having the KPI compare an individual operator’s performance to that of the best operator this will enables mining companies to identify operators that need training. In addition, this KPI can be used by all mining companies to quantify the impact of any piloted advanced technologies.
Lastly, a methodology to investigate the extent to which different levels of shovel automation can improve shovel performance is developed. Using the developed discrete event simulation model four levels of automation are evaluated. Result showed a potential 40.6% increase in production through successful development and deployment of an autonomous shovel. It is envisioned that in some situations there is an opportunity to reduce the shovel fleet size without compromising production level.
- Graduation date
- Spring 2021
- Type of Item
- Doctor of Philosophy
- This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.