AQL vs. OQL: Understanding AQL Acceptance Quality Limits and Why OQL Is a Better Predictor of Real Quality

AQL Acceptance Quality Limit has been the industry standard for decades. However, as customer expectations grow and defect tolerance shrinks, many manufacturers are shifting to a more accurate and predictive metric: OQL Observed Quality Level. Quality teams often rely on sampling plans to decide whether to accept or reject a supplier’s shipment.

This article explains AQL in simple terms, includes an easy calculation example, and shows why OQL gives you a far clearer and honest picture of your actual quality performance.

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What Is AQL Acceptance Quality Limit?

AQL Acceptance Quality Limit is the maximum percentage of defects considered acceptable in a production batch.
You inspect a sample—not the entire shipment—and decide whether to accept or reject the lot based on the number of defects you find.

Common AQL Acceptance Quality Limit values:

• 0.065% → Very strict (medical, aerospace)

• 0.4% – 1.0% → General consumer goods

• 2.5% → Less strict, often used for visual or cosmetic checks

AQL is a statistical tool that helps organizations make decisions without inspecting every piece.

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How AQL Sampling Works

1. Decide your inspection level (e.g., Level II, general inspection).

2. Determine lot size (e.g., 10,000 units).

3. Select the sample size from the AQL table (e.g., 200 units).

4. Use the AQL chart to find:

   • Acceptance number (Ac)

   • Rejection number (Re)

If defects found ≤ Ac → Accept
If defects found ≥ Re → Reject

This protects the buyer while minimizing inspection workload.

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AQL Calculation Example

Scenario:
Lot size: 10,000 units
AQL level: 1.5
Inspection level: II

Step 1: Determine sample size code
For a lot size of 10,000 with Level II, the letter code is L.

Step 2: Determine sample size
Letter code L corresponds to a sample size of 200 units.

Step 3: Use the AQL table
For AQL 1.5 and sample size 200:

• Acceptance number (Ac): 7

• Rejection number (Re): 8

Step 4: Inspect the sample
If inspectors find 7 or fewer defects, the lot passes.
If they find 8 or more, the lot fails.

Example Outcome:
You inspected 200 items and found 6 defects → The shipment passes under AQL rules.

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The Problem With AQL: It Can Hide Real Quality Issues

AQL Acceptance Quality Limit is useful but often misunderstood. Many teams believe AQL guarantees a defect rate. It does not.

AQL is NOT a measure of the actual defect rate in a shipment.
It only defines a sampling boundary for acceptance.

AQL has two common weaknesses:

1. A shipment can pass AQL inspection even with a high actual defect rate

Example:
6 defects in a 200-piece sample = 3% observed defect rate.
But the lot still passes under AQL 1.5, even though the real defect rate might be too high for your customers.

2. AQL Acceptance Quality Limit only tells you “pass/fail,” not actual quality performance

You do not get insight into:

• Trends

• Supplier stability

• Defect severity

• Predictive risk

AQL was designed for acceptance, not for improvement.

That is where OQL becomes more meaningful.

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What Is OQL (Observed Quality Level)?

OQL (Observed Quality Level) is the actual defect percentage discovered during sampling, not the theoretical threshold.
It is calculated directly from inspection results.

OQL Formula

Example Using the Same Scenario:

Sample size: 200
Defects found: 6

Even though the lot passed under AQL rules, the real observed defect level is 3%, which might be too high for your standards or your customer’s expectations.

OQL exposes the real performance.

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Why OQL Is a Better Predictor of Quality Than AQL

1. OQL reflects actual quality, not statistical allowance

AQL sets a threshold.
OQL measures what is actually happening.

2. OQL helps identify trends and recurring problems

Suppliers may pass AQL repeatedly even with rising defect trends.
OQL exposes this immediately.

3. OQL shows true risk to customers

AQL might say “pass,” but OQL shows whether customers may still receive defective units.

4. OQL supports continuous improvement programs

OQL works well with CAPA, Pareto analysis, supplier scorecards, and process audits.

5. OQL is simple, transparent, and easy to explain

Any quality manager or auditor can interpret OQL without statistical training.

6. OQL aligns with real-world quality objectives

Organizations want zero defects, not “acceptable levels.”

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AQL vs. OQL: A Quick Comparison

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AQL Acceptance Quality Limit is valuable for quick pass/fail decisions, but it does not reveal true supplier performance or predict future issues.
In contrast, OQL shows the real defect level found during inspection, making it a stronger, more honest indicator of quality.

Organizations that want deeper visibility, better supplier partnerships, and data-driven decisions use OQL alongside AQL to ensure stable, predictable, and customer-ready products.

How Lyons Quality Audit Tracking System LQATS Handles OQL (Observed Quality Level)

LQATS makes OQL automatic, visible, and actionable.

The Lyons Quality Audit Tracking System calculates OQL for every supplier audit and inspection. Instead of leaving teams to compute percentages manually, LQATS turns OQL into a live metric that appears everywhere suppliers are evaluated.

Here’s how the system handles it:

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1. Automatic OQL Calculation

As soon as you enter:

• Sample size

• Number of defects

• Defect categories

LQATS calculates OQL automatically in real time.
No spreadsheets. No manual math.

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2. OQL Used in Supplier Scorecards

Every supplier gets an OQL trend line showing:

• Average defect level

• Variation over weeks/months

• Peaks and declines

• Performance by product, line, or defect type

Suppliers with rising OQL values trigger alerts, helping you act before major failures occur.

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3. Drill-Down OQL by Defect Type

LQATS breaks OQL into:

• Critical defects

• Major defects

• Minor defects

This helps teams understand whether small cosmetic issues or serious safety issues are driving quality decline.

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4. OQL + CAPA Integration

When OQL crosses a threshold:

• LQATS automatically flags the audit

• A CAPA task can be generated

• Suppliers must submit root cause and corrective actions

• Verification and closure are tracked digitally

This aligns OQL with real corrective actions—not just reporting.

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5. Predictive Quality Analytics

LQATS uses OQL trends to:

• Identify high-risk suppliers

• Pinpoint unstable production lines

• Highlight recurring defect categories

• Predict future failures

This makes OQL a forward-looking quality indicator, not just historical data.

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6. OQL Thresholds for Pass/Fail

Teams can set internal OQL thresholds such as:

• ≤ 0.5% → Excellent

• 0.5–1.5% → Acceptable

• 1.5–3% → Needs review

• 3% → Failing / CAPA required

This gives you more control than traditional AQL rules.

Why LQATS + OQL Gives Stronger Supplier Control

Honest view of actual defect levels
Better prediction of future quality issues
Stronger supplier management
Full integration with CAPA and audit workflows
Faster decisions for accept/reject
Transparent reporting for customers and regulators
Ability to compare suppliers objectively

AQL Acceptance Quality Limit tells you “This lot passes.”
OQL tells you “This is the true quality we’re getting.”
LQATS brings both together—but uses OQL to drive real improvement.

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Conclusion

AQL Acceptance Quality Limit is useful for quick pass/fail decisions, but it often hides real defect levels. OQL provides a clear, accurate picture of actual quality, making it a better predictor of supplier performance and customer satisfaction.

With Lyons Quality Audit Tracking System, OQL becomes a powerful, automated metric—embedded into dashboards, scorecards, CAPA workflows, and predictive analytics—giving you a complete and reliable view of supplier quality.