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Use case video

Distillation Column Trip

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Reading time:
Watch time:
11
min.

This video demonstrates how TrendMiner's self-service analytics can be used to diagnose and prevent recurring trips in a distillation column, improving overall equipment effectiveness (OEE) and reducing costs.

The Problem:

  • A distillation column was experiencing periodic, automatic shutdowns.
  • The shutdowns were triggered by a "High-High" temperature alarm.
  • This alarm was caused by the "Light Steam" flow measurement dropping to zero. When the flow meter failed, the control system would fully open the steam valve in an attempt to compensate, causing the temperature to spike and trip the system.
  • Operators had very little time to react between the initial alarm and the final shutdown.

The Investigation & Solution:

  • Finding the Pattern: Using TrendMiner, an engineer analyzed the historical data for the steam flow, temperature, and other relevant process variables. They used the Similarity Search feature to identify all instances of the trip event. This confirmed the issue was happening frequently, about once a week.
  • Identifying the Root Cause: The analysis revealed a consistent precursor to the failure: a brief but significant pressure spike in the main steam network occurred shortly before the steam flow meter would drop out. This pressure spike was identified as the root cause of the flow meter malfunction.
  • Creating an Early Warning: Since the steam network pressure spikes could not be eliminated, the engineer created a "fingerprint" of this specific sequence of events (pressure spike, followed by the initial temperature rise).
  • Proactive Monitoring: This fingerprint was then used to set up an active monitor. Now, whenever TrendMiner detects this specific pattern starting to occur, it automatically sends an early warning notification (via email or an in-app alert) to the operations team.

The Benefits & Results:

  • Preventing Shutdowns: The early warnings give operators enough time to take corrective action before the column trips, preventing costly downtime.
  • Improved OEE: By avoiding shutdowns, the overall equipment effectiveness is significantly improved.
  • Reduced Costs: The solution reduces operational and maintenance costs associated with emergency shutdowns and restarts. It also minimizes thermal and physical stress on the equipment.
  • Enhanced Safety: Proactively managing the process reduces the risk of safety incidents.
  • Immediate Impact: The plant was able to avoid several shutdowns within the first month of implementing the monitoring system.

All industries
Asset Performance Management
Operational Performance Management
Process Optimization
Production Reporting
Trend Client / Data Discovery
Process Engineer
Plant Manager
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This video demonstrates how TrendMiner's self-service analytics can be used to diagnose and prevent recurring trips in a distillation column, improving overall equipment effectiveness (OEE) and reducing costs.

The Problem:

  • A distillation column was experiencing periodic, automatic shutdowns.
  • The shutdowns were triggered by a "High-High" temperature alarm.
  • This alarm was caused by the "Light Steam" flow measurement dropping to zero. When the flow meter failed, the control system would fully open the steam valve in an attempt to compensate, causing the temperature to spike and trip the system.
  • Operators had very little time to react between the initial alarm and the final shutdown.

The Investigation & Solution:

  • Finding the Pattern: Using TrendMiner, an engineer analyzed the historical data for the steam flow, temperature, and other relevant process variables. They used the Similarity Search feature to identify all instances of the trip event. This confirmed the issue was happening frequently, about once a week.
  • Identifying the Root Cause: The analysis revealed a consistent precursor to the failure: a brief but significant pressure spike in the main steam network occurred shortly before the steam flow meter would drop out. This pressure spike was identified as the root cause of the flow meter malfunction.
  • Creating an Early Warning: Since the steam network pressure spikes could not be eliminated, the engineer created a "fingerprint" of this specific sequence of events (pressure spike, followed by the initial temperature rise).
  • Proactive Monitoring: This fingerprint was then used to set up an active monitor. Now, whenever TrendMiner detects this specific pattern starting to occur, it automatically sends an early warning notification (via email or an in-app alert) to the operations team.

The Benefits & Results:

  • Preventing Shutdowns: The early warnings give operators enough time to take corrective action before the column trips, preventing costly downtime.
  • Improved OEE: By avoiding shutdowns, the overall equipment effectiveness is significantly improved.
  • Reduced Costs: The solution reduces operational and maintenance costs associated with emergency shutdowns and restarts. It also minimizes thermal and physical stress on the equipment.
  • Enhanced Safety: Proactively managing the process reduces the risk of safety incidents.
  • Immediate Impact: The plant was able to avoid several shutdowns within the first month of implementing the monitoring system.

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