- UAE (Dubai): 29/8-2/9/22
- FINLAND (Kuopio): 3-7/10/22
- SPAIN (Oviedo): 31/10-4/11/22
- UAE (Dubai): 18-22/11/22
- TURKEY (Istanbul): 18-22/11/22
Mine-to Mill Grade Control
This course will be completed using a mix of theoretical concepts, best practice case studies, and practical activity work, to reinforce knowledge and concepts explored during the course. Participants are assumed to be familiar with a mining environment and are comfortable with basic calculations and statistics.
The course equips participants with the knowledge pertaining to how Grade Control generates value at producing mines. In addition, best practice in grade control techniques to minimise misclassification of ore and waste are considered. Other important datasets which are information sources for predicting orebody behaviour are considered.
Grade Control is an integral part of orebody exploitation. The key tool in grade control is the Grade Control Model (GCM) and remains critical to ore/waste definition and material destination direction as economic parameters such as CoG or NSR can be built into it. During grade control, certain estimation techniques must be utilised that ensure that the estimated grade-tonnage (G-T) relationship of the orebody reflects the anticipated mining selectivity. The course will also look at why the grade control model and resource model are different.
Ore control and management of stockpiles are also examined in detail.
- The Grade Control Process Defined
- Overview of the Grade Control System
- Data Collection Considerations
- Grade Control Sampling Techniques
- Grade Control Quality Control Systems
- Assays, Bulk Density and Moisture
- Database Management and Data Security
- Grade Control Modelling
- Costs and Cut-Off Grades
- Selectivity and Ore/Waste Definition
- Dig Plans
- Mark Outs and Ore Spotting
- Blast Movement Monitoring
- Stockpiles Management
- Procedural Issues to watch out for
Key Learning Objectives
- Grade Control, Deposit Geology And Mining Methods
- Grade Control Sampling Considerations
- Cut-Off Grades
- Grade Control Model Block Size And Drilling Grid Optimisation
- Selectivity, Polygonal/Kriging Techniques And Dig Plan Generation
- Ore Control And Stockpiles Management
- Learn how to;
- monitor and adjust for blast movement.
- manage stockpiles.
- manage the blending strategy.
- manage mining practices to minimise misclassification.
This course will be completed using a mix of theoretical concepts, best practice case studies, and practical activity work, to reinforce knowledge and concepts explored during the course. Participants are assumed to be familiar with a mining environment and are comfortable with basic calculations and statistics. The course is designed to run over 2 working weeks (10 days), is self-paced, inclusive of live online lectures, online practical work and offline assignments.
Mine reconciliation is a scientific and objective method used to determine whether the assumptions built into predictions are valid and whether they can be used to increase the accuracy of mine planning while improving orebody knowledge. It is also a crucial management tool to identify and explain problems, and ultimately justify improvements to current practices. A robust quantitative reconciliation system will mining operation to realise, over time, the true value of the deposits they are exploiting, by measuring production performance against production targets, and assessing the strength of how they are evaluating their mineral assets.
The objective of mining reconciliation is not to get two sets of numbers to balance, which is often seen as an end in itself by those focused on factors, but rather to help identify and understand the discrepancies that occur throughout the reconciliation process, in order to assess and improve the processes involved. Mining reconciliation is a powerful tool that can identify problems with physical measures such as blasting, mining, stockpile balancing or metallurgical processing. A good reconciliation system has checks and controls in place to ensure that performance measures are robust and allow for effective assessment of the various mining predictive models.
The course introduces the mining value chain (MVC), measurement points along the MVC, reconciliation between points in the value chain and between periods in the Life-of-Mine. Participants will also learn where errors can occur in a reconciliation system, how best to deal with them, and how to improve communicating reconciliation results.
- Mine Value Chain
- Material Movement Flow
- Process Flow Management
- Reconciliation as a Quality Control Tool.
- Ore Flows, Risk Assessment, Sampling
- Measurement Points in the Value Chain
- Standard Reconciliation Nomenclature
- Point to Point Reconciliation – Data and Calculations
- Period On Period Reconciliation – Data and Calculations
- The Reconciliation Systems
- Software Tools for Data Management and Analyses
Key Learning Objectives
- Understanding The Mine Value Chain
- Process Mapping
- Mine Reconciliation Calculations And Analyses
- Leveraging Mine Reconciliation Data