1. False Acceptance: When Nonconforming Product Is Released

False acceptance occurs when measurement error masks a nonconformance, allowing a defective or marginal product to be released to the customer. 

What Happens 

• Measurement results appear compliant 
• Actual product performance falls outside requirements 
• Issues surface during customer use, not internal inspection 

Because the data appeared valid at release, organizations often discover false acceptance only after complaints, failures, or audits. 

The Business Impact 

• Field failures 
• Warranty claims 
• Customer disruption 
• Product recalls 

Recalls driven by false acceptance are especially costly because the issue is not confined to a single lot—it often affects all product released under the same measurement conditions. 

2. False Rejection: When Good Product Is Scrapped

False rejection occurs when measurement error causes compliant product to be identified as nonconforming. 

What Happens 

• Measurement systems overstate deviation 
• Operators adjust stable processes unnecessarily 
• Product that meets customer requirements is scrapped or reworked 

False rejection is often normalized as “the cost of quality,” even though it is driven by avoidable measurement risk. 

The Business Impact 

• Increased scrap and rework 
• Reduced yield 
• Unnecessary material and labor costs 
• Artificial capacity constraints 

False rejection quietly erodes margins while providing no improvement in customer satisfaction. 

3. Neglected Quality Systems Amplify Both PFA and PFR

Poor calibration increases uncertainty and variability in measurement systems. When uncertainty is poorly characterized or ignored, decision rules become unreliable. 

What Happens 

• Measurement uncertainty is underestimated or misunderstood 
• Acceptance criteria are applied without risk consideration 
• Decision thresholds are treated as absolute rather than probabilistic 

This environment increases the likelihood of both false acceptance and false rejection simultaneously. 

The Business Impact 

• Conflicting quality signals 
• Loss of confidence in inspection results 
• Ineffective process control 

Organizations end up paying twice: once for scrap, and again for failures that escape detection. 

4. Product Recalls Are Often Measurement Failures in Disguise

Many recalls are triggered not by confirmed defects, but by an inability to defend historical measurement decisions. 

What Happens 

• A customer complaint or audit raises questions 
• Calibration data cannot support prior acceptance decisions 
• The scope of impact cannot be confidently limited 

When measurement integrity cannot be demonstrated, organizations are forced to assume worst-case exposure. 

The Business Impact 

• Broad recall of potentially unaffected product 
• Customer production shutdowns 
• Regulatory involvement 
• Long-term damage to brand credibility 

In these cases, the recall cost is driven less by product performance and more by loss of measurement confidence. 

5. Over-Control Is a Common Reaction to Measurement Uncertainty

When organizations recognize measurement risk—without addressing its root cause—they often compensate by tightening internal controls. 

What Happens 

• Internal acceptance limits become more restrictive than customer requirements 
• Operators make frequent adjustments “to be safe” 
• Processes become unstable 

This reactive approach increases PFR while doing little to reduce PFA. 

The Business Impact 

• Reduced throughput 
• Higher operational costs 
• Increased human error 

Measurement uncertainty should be managed analytically—not through over-control. 

6. Calibration Quality Directly Influences Decision Risk

Calibration is the foundation of decision confidence. When calibration is treated as a commodity, decision risk increases. 

What Happens 

• Uncertainty statements are generic or indefensible 
• Decision rules are not aligned with measurement capability 
• Calibration certificates satisfy paperwork but not risk analysis 

This creates a false sense of security while increasing exposure. 

The Business Impact 

• Ineffective inspection systems 
• Audit findings 
• Escalating corrective actions 
• Erosion of customer trust
   

Choose Calibration Equipment and Calibrations That Reduce PFA and PFR 

A calibration provider that supports customer deliverables should: 

• Provide transparent, defensible uncertainty analysis 
• Understand decision risk—not just compliance 
• Support risk-based acceptance criteria 
• Help reduce both false acceptance and false rejection 

Calibration should strengthen product release decisions—not undermine them. 

 Examples of Measurement and Quality Failures 

History provides clear examples of what happens when measurement systems are trusted without adequate controls, validation, or risk awareness. 

Patriot Missile Failure (1991, Gulf War) 
A small timing error in the Patriot missile defense system accumulated over extended operation, eventually causing the system to miscalculate target position. Because the measurement error was not adequately corrected or recalibrated over time, valid threats were falsely assessed as non-threatening. The system failed to intercept an incoming missile, resulting in the loss of 28 lives. 
Lesson: Small, unmanaged measurement errors can accumulate into catastrophic failures. 

NASA’s Mars Climate Orbiter (1999) 
The Mars Climate Orbiter was lost due to incompatible measurement units used by different teams. Navigation data appeared valid and passed review, but the underlying measurement assumptions were incorrect. The spacecraft entered Mars’ atmosphere at the wrong altitude and was destroyed, ending a $327 million mission. 
Lesson: Measurement data that appears compliant can still be fundamentally wrong if underlying assumptions are not controlled. 

Boeing 737 MAX Crashes (2018–2019) 
The 737 MAX flight control system relied on data from a single angle-of-attack sensor. When that sensor produced erroneous measurements, the system accepted the data as valid and repeatedly commanded unsafe aircraft behavior. The result was two fatal crashes, the loss of 346 lives, and billions of dollars in financial and reputational damage. 
Lesson: Overreliance on unverified measurement inputs dramatically increases the probability of false acceptance. 

Common Thread 
Each of these failures was not caused by a single bad component, but by systems that accepted incorrect measurement data as trustworthy. In all three cases, false acceptance of flawed measurement inputs propagated through decision-making systems until the consequences became irreversible. 

These events underscore a critical reality: measurement confidence is inseparable from risk management. When calibration and measurement controls fail, the cost is measured not only in dollars—but in lives, trust, and long-term credibility. 

Final Thoughts 

False acceptance and false rejection are not abstract statistical concepts. They are financial and reputational risks that affect every customer deliverable released based on measurement data. 

The true cost of poor calibration appears as: 

• Scrap and rework 
• Customer complaints 
• Product recalls 
• Regulatory and audit exposure 
• Lost confidence and revenue 

For organizations that rely on measurement to release product, calibration quality is inseparable from business performance. 

At Richard J. Bagan, Inc., calibration is treated as a risk management function focused on reducing PFA and PFR—because every customer deliverable depends on reliable, risk-informed measurement decisions.