Publication: Minerals Engineering

Edition: 99 (2016) 76–88

Date:  26 September 2016

Paper: Value Driven Methodology to Assess Risk and Operating Robustness for Grade Engineering Strategies by means of Stochastic Optimisation

           
 

Title:

Value Driven Methodology to Assess Risk and Operating Robustness for Grade Engineering Strategies by means of Stochastic Optimisation

 Category:

Grade Engineering

 

       
 

Author:

Carrasco, C1,2*., Keeney, L1,2., Scott, M1,. Napier-Munn, T.J2.

 

       
 

Affiliations:

1. Co-operative Research Centre for Optimising Resource Extraction (CRCORE), Brisbane, Australia.
2. Julius Kruttschnitt Mineral Research Centre (JKMRC), The University of Queensland, Brisbane, Australia.

 

       
 

Abstract text:

Grade Engineering® spans a range of operational techniques that exploits intrinsic grade variability to remove low grade uneconomic material prior to energy intensive and inefficient grinding.

Grade Engineering provides an additional level of operational flexibility whilst also incurring complexity that needs to be managed for an effective operational deployment. An integrated value driven methodology has been developed to manage this complexity by means of stochastic optimisation. This allows the optimum Grade Engineering processing “recipe” to be determined that maximises value per unit of time that can be drawn from a production volume under a set of user defined constraints. The introduction of uncertainty in the stochastic optimisation problem enables the assessment of the risk and operating robustness, both essential in robust decision-making processes.

The case study discussed in the paper comprises a large open cut copper porphyry deposit for which two Grade Engineering strategies are assessed: differential blasting for grade, and preferential grade by size response. These size-based coarse separation levers are subsequently exploited through a Grade Engineering circuit. This comprises a set of screens and crushers, with a configuration and operating settings defined by the Grade Engineering recipe.

The methodology developed demonstrated that size-based Grade engineering is a robust operating option that can effectively deliver significant improvements in unit metal productivity.

Keywords: Physical Separation, Mineral Economics, Stochastic Optimisation, Decision Support Systems.

 

       
 

Contact us:

Cooperative Research Centre Optimising Resource Extraction (CRC ORE)

 

       

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