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Use case

Stabilizing Stripper Level Control: Root Cause Analysis of Sudden Column Level Variations

Pablo Sanchez
,
Industry Principal
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3
min.

The Challenge

The stripper column level had been unstable for some time. Sudden increases and decreases triggered the advanced control system to intervene aggressively, disturbing overall production to stabilize column variables. What initially seemed like random oscillations were repeatedly affecting throughput and operational confidence.

The team needed to understand why these abrupt level shifts were occurring and whether they were linked to specific operating conditions or system changes.

  • Sudden stripper level fluctuations
  • Advanced control interventions impacting production
  • No clear trigger identified
  • Ongoing operational instability

The Approach

Engineers structured the investigation using data-driven filtering and variance analysis.

  • Production filtering: Non-production periods were removed to focus only on relevant operating conditions
  • Variance calculation: An aggregated formula tag was created to quantify stripper level variability
  • Event search: Periods with similar variance patterns were identified across historical data
  • Change correlation: Analysis revealed that instability began after a process control unit upgrade
  • Influence factor identification: Temperature and reflux flow were identified as key drivers affecting level behavior
Periods with similar variance patterns identified across months or years of historical data

Key Insight

The instability was not random, it was linked to specific process variables and coincided with a control system upgrade.

Results

KPIResult
Root cause triggerControl system upgrade identified
Key influence factorsTemperature and reflux flow
Diagnostic methodVariance-based search and filtering
Operational clarityClear explanation of level shifts
Control improvementTargeted parameter adjustment possible

The Takeaway

By isolating the drivers of stripper level instability, the team regained control over column behavior, reduced unnecessary control interventions, and improved production stability through targeted parameter optimization.

Oil & gas
Energy & natural resources
Operational Performance Management
Process Optimization
Process Health Monitoring
Process Engineer
Automation Engineer
Operator
Plant Manager
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The Challenge

The stripper column level had been unstable for some time. Sudden increases and decreases triggered the advanced control system to intervene aggressively, disturbing overall production to stabilize column variables. What initially seemed like random oscillations were repeatedly affecting throughput and operational confidence.

The team needed to understand why these abrupt level shifts were occurring and whether they were linked to specific operating conditions or system changes.

  • Sudden stripper level fluctuations
  • Advanced control interventions impacting production
  • No clear trigger identified
  • Ongoing operational instability

The Approach

Engineers structured the investigation using data-driven filtering and variance analysis.

  • Production filtering: Non-production periods were removed to focus only on relevant operating conditions
  • Variance calculation: An aggregated formula tag was created to quantify stripper level variability
  • Event search: Periods with similar variance patterns were identified across historical data
  • Change correlation: Analysis revealed that instability began after a process control unit upgrade
  • Influence factor identification: Temperature and reflux flow were identified as key drivers affecting level behavior
Periods with similar variance patterns identified across months or years of historical data

Key Insight

The instability was not random, it was linked to specific process variables and coincided with a control system upgrade.

Results

KPIResult
Root cause triggerControl system upgrade identified
Key influence factorsTemperature and reflux flow
Diagnostic methodVariance-based search and filtering
Operational clarityClear explanation of level shifts
Control improvementTargeted parameter adjustment possible

The Takeaway

By isolating the drivers of stripper level instability, the team regained control over column behavior, reduced unnecessary control interventions, and improved production stability through targeted parameter optimization.

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Share with a co-worker

The Challenge

The stripper column level had been unstable for some time. Sudden increases and decreases triggered the advanced control system to intervene aggressively, disturbing overall production to stabilize column variables. What initially seemed like random oscillations were repeatedly affecting throughput and operational confidence.

The team needed to understand why these abrupt level shifts were occurring and whether they were linked to specific operating conditions or system changes.

  • Sudden stripper level fluctuations
  • Advanced control interventions impacting production
  • No clear trigger identified
  • Ongoing operational instability

The Approach

Engineers structured the investigation using data-driven filtering and variance analysis.

  • Production filtering: Non-production periods were removed to focus only on relevant operating conditions
  • Variance calculation: An aggregated formula tag was created to quantify stripper level variability
  • Event search: Periods with similar variance patterns were identified across historical data
  • Change correlation: Analysis revealed that instability began after a process control unit upgrade
  • Influence factor identification: Temperature and reflux flow were identified as key drivers affecting level behavior
Periods with similar variance patterns identified across months or years of historical data

Key Insight

The instability was not random, it was linked to specific process variables and coincided with a control system upgrade.

Results

KPIResult
Root cause triggerControl system upgrade identified
Key influence factorsTemperature and reflux flow
Diagnostic methodVariance-based search and filtering
Operational clarityClear explanation of level shifts
Control improvementTargeted parameter adjustment possible

The Takeaway

By isolating the drivers of stripper level instability, the team regained control over column behavior, reduced unnecessary control interventions, and improved production stability through targeted parameter optimization.

Access now

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