Metal Balance of Cu-Co Tailings Reclamation
WGA applied advanced tools to deliver an interactive metal balance dashboard for a complex copper cobalt tailings reclamation plant in Africa. Recommendations to improve the accuracy of the site metal accounting impacted definition of ~$300M USD per annum of product. Working alongside the Owner’s Team, WGA were able to offer optimisation and automation for existing metal accounting processes and procedures. WGA’s unique mix of experienced metallurgists and data experts ensured a robust product compliant to AMIRA P754 Metal Accounting Code of Practice.
WGA produced an interactive Grafana dashboard to communicate daily metal flows, daily metal content in inventory, and month end balance for a complex copper cobalt tailings reclamation plant in Africa. Recommendations to improve the accuracy of the site metal accounting were made due to WGA’s metal balance, which was developed in python code. Implementation of the recommendations to improve accuracy would account for approximately $300M USD per annum of product. Single and four node metal balances were performed using error minimization, to deliver a deeper understanding of metal content movement and areas requiring further investigation. The WGA team produced comprehensive block flow diagrams and online dashboards in Grafana and Power BI. Plant diagnostic dashboards were also developed to perform on-the-go diagnostics of discrepancies.
Audit of the existing data pipeline and the metallurgical accounting processes identified recommendations in:
- SCADA instrument data sampling frequency
- Stream instrumentation and assay results error propagation
- Statistical analysis of key stream inputs
- Fundamental process assumptions and metal content inventory movement
- Compliance status with the AMIRA P754 Metal Accounting Code of Practice
- Data pipeline limitations and opportunities to improve efficiency and traceability
"WGA’s specialists in data analytics designed a systematic and auditable data pipeline and architecture, including a semi-automated cloud-based data flow from assay templates and Scada inputs included data wrangling and storage of results in a secure Azure database."