An integrated “Mine to Mill” automation methodology applied to Sanbrado

Jennings, Clinton (2022) An integrated “Mine to Mill” automation methodology applied to Sanbrado. [USQ Project]

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This report aims to determine the potential and best practice for an integrated “mine to mill” complete site control methodology based on real-time changing requirements and data. The West African Resources “Sanbrado” operation will be the benchmark.

Active mining operations can be split into mining and processing activities. At the same time, each of these groups has its own internal goals, key performance indicators and internal efficiency measures. There is little active “real-time” feedback between the operation’s two phases.

This report aims to examine what information is currently utilised, what information could be utilised and what improvements could be gained by integrating the existing control methodologies of each phase of the operation to create an integrated single-process control arrangement in the form of a hypervisor style arrangement.

From an overall site control system standpoint, each department, mining and processing currently act as a closed feedback control system. However, the closed feedback loops stay within their departments. From a combined perspective, they serve to work as an open feedback control system to each other.

This project seeks to analyse both mining and processing control methodology separately, breaking each department into their respective control feedback diagrams and examining desired current and potential improved inputs and variables, examining efficient outputs for each department. Once achieved, combine each department’s process control philosophy into a closed-loop control system across the entire mining operation without interference with existing functional operations.

The key finding of this project is the concept of optimised blasting. Increasing or decreasing explosives can have significant cost savings across the entire operation. To achieve optimised blasting more accurately, real-time ore hardness data could be used as opposed to the concepts theory of just checking operational costs periodically.

To achieve more accurate optimised blasting, real-time data capture and processing of fragmentation, crushing and milling work index values must be captured. Furthermore, the captured data needs to be pointed back to a mining location so the data can be appropriately assigned.

More than just the implementation of additional instrumentation and data storage is required to create this data. SAG mill “Semi Autogenous mill” work index has a high variance with respect to accurate results. Steps to rectify the variance need to be taken.

These improvements should improve productivity by building cooperation and efficiency and potentially gain a more accurate operating cost analysis. It can have financial benefits by increasing cost prediction accuracy for mining operations.

It’s estimated from the analysis that potentially, a total benefit of an increase in production rates of 9.5% on existing data is possible once fully implemented. This creates a payback rate of less than one year on investment, making this type of control highly viable.

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Item Type: USQ Project
Item Status: Live Archive
Faculty/School / Institute/Centre: Current – Faculty of Health, Engineering and Sciences - School of Engineering (1 Jan 2022 -)
Supervisors: Low, Tobias
Qualification: Bachelor of Engineering (Honours) (Instrumentation and Control)
Date Deposited: 19 Jun 2023 03:45
Last Modified: 20 Jun 2023 01:09
Uncontrolled Keywords: mining operations; "mine to mill"; mining; processing

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