Inconsistent phosphate recovery rates in rougher flotation circuits.
Laboratory results available only every 12 hours.
Operators relying on experience for parameter adjustments.
Goal to improve flotation plant recovery by 1% without sacrificing OEE or quality.
Gathered 5 years of historical data from multiple sources (PI, LIMS, legacy systems). Identified 57 key attributes, including lagged variables for predictive sustainability.
Developed an ensemble model (Model A) for complex predictions. Created a leaner model (Model B) for simulating recovery. Achieved desired recovery improvement goals.
Deployed models into the production environment. Integrated with existing systems for seamless operation. Provided training and support for end-users.
Monitored model performance and made necessary adjustments. Conducted regular reviews to ensure alignment with business goals. Leveraged feedback for ongoing enhancements.
By leveraging Process Point’s expertise in data-driven intelligence, the client successfully optimized their flotation recovery process. This case study demonstrates the power of advanced analytics and real-time monitoring in solving complex industrial challenges, leading to significant improvements in mineral recovery. The implementation not only achieved the client’s goal but also provided long-term benefits through enhanced decision-making capabilities and operational insights.
