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Why Measurement System Analysis (MSA) Matters

2025-01-15•By Dr. Ken Bertagnolli
MSAQuality ControlBest Practices

Before you invest time and resources in any data collection effort, you need to ask a critical question: Can you trust your measurements?

This is where Measurement System Analysis (MSA) comes in. MSA is a statistical method used to evaluate the accuracy, precision, and stability of your measurement system.

The Hidden Cost of Poor Measurements

Many organizations unknowingly make decisions based on faulty measurement systems. The consequences can be severe:

  • False alarms - Investigating problems that don't exist
  • Missed problems - Failing to detect real issues
  • Wasted resources - Time spent collecting unreliable data
  • Poor decisions - Conclusions based on measurement noise rather than real process variation

What MSA Evaluates

A good MSA study examines several key characteristics:

Accuracy (Bias)

Is your measurement system hitting the true value on average? If you're measuring a known standard, does your system report the correct value?

Precision (Repeatability)

If the same operator measures the same part multiple times, how consistent are the results? High repeatability means your equipment is reliable.

Reproducibility

If different operators measure the same part, do they get similar results? Poor reproducibility suggests operator technique or training issues.

Stability

Does your measurement system maintain its accuracy and precision over time? Regular calibration and maintenance are essential.

When to Conduct MSA

You should perform MSA:

  • Before starting any major data collection effort
  • When implementing a new measurement system
  • When results seem questionable or inconsistent
  • Periodically as part of quality system maintenance
  • Before conducting a Design of Experiments (DOE) study

The MSA Process

  1. Select representative parts - Choose items that span your measurement range
  2. Design the study - Typically involves multiple operators and repeated measurements
  3. Collect data systematically - Follow a randomized measurement plan
  4. Analyze results - Calculate gage R&R and other statistics
  5. Take action - Improve the measurement system if needed

Rule of Thumb

A general guideline is that your measurement system should account for less than 10% of the total variation you're trying to measure. If measurement error is greater than 30%, the system is unacceptable and must be improved before proceeding.

Learn More

Objective Experiments offers comprehensive MSA training that covers both the theory and practical application. Our students learn how to design MSA studies, interpret results, and improve their measurement systems.

Interested in MSA training? Explore our MSA course or contact us for more information.