How Engineers Perform Root Cause Analysis for Packed Tower Problems

Packed tower problems often appear as simple symptoms:

• higher pressure drop;
• lower separation efficiency;
• product quality deterioration;
• increased energy consumption.

However, the visible symptom is not always the real cause.

For example:

A higher pressure drop does not automatically mean:

“The packing is blocked.”

Possible causes include:

• higher gas load;
• liquid maldistribution;
• fouling;
• internal damage;
• changed operating conditions.

The engineering question is:

How do engineers identify the real cause behind packed tower performance problems?

The key principle is:

Effective troubleshooting requires finding the root cause instead of only correcting the visible symptom.

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Why Root Cause Analysis Matters

A temporary correction may restore operation briefly.

But if the underlying cause remains:

• the problem returns;
• maintenance cost increases;
• reliability decreases.

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1. Define the Problem Clearly

A good RCA starts with a precise problem statement.

Example:

Poor:

“Tower performance is bad.”

Better:

“Pressure drop increased from 250 Pa/m to 450 Pa/m over six months at the same production rate.”

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2. Compare Current Condition With Normal Operation

Engineers review:

• previous operating data;
• design condition;
• recent changes.

The goal:

identify what changed before the problem appeared.

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3. Separate Process Causes From Equipment Causes

A performance problem may come from:

Process

• flow increase;
• composition change;
• temperature change.

Equipment

• packing damage;
• distributor problem;
• fouling.

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4. Analyze Pressure Drop Problems

Possible causes:

Increased ΔP With Higher Flow

Possible:

normal hydraulic response.

Increased ΔP With Same Flow

Possible:

• fouling;
• blockage;
• internal damage.

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5. Analyze Efficiency Loss Problems

Possible causes:

• poor liquid distribution;
• reduced packing area;
• wrong operating condition;
• process change.

Efficiency loss does not always mean packing failure.

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6. Use Multiple Data Sources

Useful information:

• DCS operating data;
• inspection records;
• maintenance history;
• laboratory results.

One data source is usually insufficient.

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7. Build Cause-and-Effect Relationships

Example:

Symptom:

Outlet concentration increases.

Possible causes:

↓

Liquid distribution problem

↓

Less wetting

↓

Lower effective area

↓

Reduced mass transfer

This helps identify the actual mechanism.

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8. Confirm the Root Cause Before Action

A suspected cause should be tested.

Examples:

• compare operating data;
• inspect internals;
• review material condition.

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9. Avoid Common Misdiagnosis

Example:

Problem:

High pressure drop.

Wrong conclusion:

Replace packing immediately.

Possible actual cause:

Blocked distributor causing poor liquid flow.

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10. Corrective Action Should Address the Cause

Examples:

Root cause:

Fouling mechanism.

Action:

Improve pretreatment or material selection.

Not only:

Clean the packing repeatedly.

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Example 1 — Rising Pressure Drop

Observation:

ΔP increases gradually.

Data:

Flow unchanged.

Investigation:

Fouling accumulation.

Corrective action:

Cleaning + fouling prevention.

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Example 2 — Poor Absorption Efficiency

Observation:

Outlet concentration increases.

ΔP normal.

Investigation:

Liquid distributor damage.

Corrective action:

Repair distributor.

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Example 3 — Unexpected Flooding

Observation:

Tower floods earlier than design.

Investigation:

Actual gas density higher due to pressure change.

Corrective action:

Review operating conditions.

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Packed Tower Root Cause Analysis Workflow

Define Abnormal Symptom

↓

Collect Operating Data

↓

Compare With Normal Condition

↓

Separate Possible Causes

↓

Verify Root Cause

↓

Implement Corrective Action

↓

Confirm Performance Recovery

↓

Prevent Problem Recurrence

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Root Cause Analysis Checklist

Problem Definition

✓ Symptom description✓ Time of occurrence✓ Operating condition

Data Review

✓ Flow✓ Pressure drop✓ Temperature✓ Performance trend

Equipment Review

✓ Packing✓ Distributor✓ Support✓ Mist eliminator

Corrective Action

✓ Cause removed✓ Result verified✓ Prevention added

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Common RCA Mistakes

Mistake 1 — Treating Symptoms as Causes

Why it fails:

The problem returns.

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Mistake 2 — Blaming Packing First

Why it fails:

Many problems come from operation or internals.

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Mistake 3 — Using Only One Data Point

Why it fails:

A trend is needed.

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Mistake 4 — Ignoring Recent Process Changes

Why it fails:

The original design basis may have changed.

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Mistake 5 — Fixing Without Verification

Why it fails:

The true cause may remain.

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Root Cause Analysis vs Related Nodes