Diamond processing is a unique application of minerals processing, where individual particles are liberated and recovered from host ore, preferably without further breakage. Operational profitability is based on the size, quantity and perceived quality of the recovered stones.
Met Dynamics’ diamond processing solution provides deeper insight into plant performance than offered by traditional simulation tools.
Diamond processing shares many similarities with other coarse mineral processing activities, including crushing, ore scrubbing and screening operations.
However, the dilute and discrete nature of stone distribution within host ore means that internal plant streams cannot be practically sampled for diamond content.
This makes the measurement and evaluation of processing plant performance very difficult.
Traditional approaches to this problem use the host ore as a proxy for diamond deportment. This offers little insight into the degree of liberation of diamonds from the host ore throughout different areas of the plant.
Critically, it is the degree of liberation which determines the probability of recovery by subsequent dense medium separation techniques.
Met Dynamics have developed a simulation solution to tackle the diamond liberation challenge.
By extending our multicomponent comminution models we are able to predict the liberation of diamonds from blended ore during any breakage process.
The framework also allows for the liberation of heavy mineral components in the host ore, which can bottleneck dense medium separation and x-ray recovery circuits.
Our framework is based on the joint distribution theory described by R.P King, and characterised by the Andrews-Mika diagram.
Both steady-state and dynamic simulation modes are available and can incorporate process control and operating philosophies, constraint analysis, and energy and water consumption metrics.
Applications for our diamond processing framework include:
- Life-Of-Mine production and revenue planning, ore blending strategies
- Constraint analysis and debottlenecking
- Scenario evaluation for business decision support (e.g. cut-off optimisation, capital expansion options)
- Process control and operating philosophy improvements
- Quantifying energy efficiency and cost reduction opportunities
R.P. King, 2001, Modeling & Simulation of Mineral Processing Systems, Butterworth-Heinemann, Oxford, UK.