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Large industrial thickener tanks in a mining operation with processing equipment and control systems
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Improving Thickener Performance

Advanced data analysis uncovering root causes and improving reliability

Mining Operations

Advanced data analysis for equipment reliability

Mining Operation
Performance optimization project
Process Engineering
Improved
Thickener Stability
Reduced
Equipment Failures
Optimized
Wash Efficiency

Introduction

Thickeners are a critical component in many mining operations, but they are often plagued by instability, breakdowns, and inefficiency. This case study highlights how CFT applied advanced data analysis to uncover the root causes of variability and significantly improve thickener reliability.

The Challenge

The mining operation was experiencing:

Unstable mass flows leading to downstream operational issues
Frequent equipment failures, including rake lifting and torque problems
Poor wash efficiency, resulting in wasted materials

Key KPIs included:

  • Bed mass stability
  • Underflow density
  • Torque measurements

Solution

Through advanced statistical modeling, CFT identified clear patterns:

1

Flowrate Variability

Instability was traced to fluctuations in the feed flowrate.

2

Decoupled Mass Flow

The feed and underflow mass flows were operating independently, causing inconsistencies.

3

Flocculant Inefficiency

Suboptimal dosing was contributing to poor clarity and increased breakdowns.

Probability density relationships showing mass flow and flowrate correlations in thickener operations, demonstrating how variability in mass is directly tied to flowrate movements and the decoupling of feed and underflow mass flows

Probability density analysis revealing critical relationships between mass flow, flowrate, and density parameters

Advanced probability density plots showing the relationship between rate of change of mass flow and flowrate, indicating flowrate dynamics are directly tied to mass dynamics with minimal dampening effects

Detailed analysis showing how flowrate dynamics directly impact mass dynamics and contribute to thickener instability

Results Achieved

Equipment Configuration Analysis

0.95%
Efficiency Loss Only
6 vs 7 thickeners
+1.52%
Wash Efficiency Gain
0.2 higher wash ratio
+0.96%
Efficiency Improvement
2% higher specific gravity

Operational Improvements

Improved Thickener Stability
Reducing strain on mechanical components
Reduced Equipment Failures
Significant reductions in bogging and rake lifting
Minimized Torque Issues
Fewer torque-related failures

Process Optimization

Optimized Wash Efficiency
Fewer thickeners required
Direct Operational Savings
Reduced resource requirements
Enhanced Process Control
Better understanding of system dynamics

Thickener Configuration Analysis

Efficiency matrix showing performance analysis with 6 thickener configuration, displaying operational parameters and wash efficiency metrics

6 Thickener Configuration Analysis

Efficiency matrix showing improved performance analysis with 7 thickener configuration, demonstrating optimized wash efficiency and reduced resource requirements

7 Thickener Configuration Analysis

Comparative analysis showing how optimization reduced the number of thickeners required while maintaining efficiency

Key Takeaway

More equipment doesn't always mean more efficiency. By deeply understanding thickener dynamics, we uncovered a path to greater stability with fewer machines.

Technologies & Methodologies

Core Technologies
Advanced Statistical ModelingProcess AnalyticsRoot Cause AnalysisEquipment MonitoringFlow AnalysisPerformance Optimization
Analysis Approach
✓ Historical Data Analysis
✓ Pattern Recognition
✓ Correlation Analysis
✓ Process Flow Optimization
✓ Equipment Performance Monitoring
✓ Operational Insights Generation