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Overview 
Measurement System Analysis (MSA) evaluates the reliability and accuracy of a measurement system. It determines whether a system produces consistent and correct results. MSA is divided into two categories: 

• Accuracy: How close the measurement is to the true value.
• Precision: How consistent the measurements are.

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Accuracy (How Close to the True Value) 
Accuracy includes Bias, Linearity, and Stability.

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1. Bias 
- Definition: Difference between the measurement system's average value and the reference value. 
- Purpose: Detects systematic errors in measurements. 
- Key Points: 
   - Bias = Measured Average – Reference Value 
   - Generally addressed through calibration. 
   - If calibration is done correctly, bias studies may not be required. 

- Graph: Shows the offset between the measurement system average and the reference value.

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2. Linearity 
- Definition: The change in bias over the normal operating range. 
- Purpose: Determines whether bias remains consistent across the operating range. 
- Key Points: 
   - Poor linearity means bias varies across the range. 
   - Requires at least 3 points in the operating range for analysis. 

- Graph: Compares perfect linearity (constant bias) with poor linearity.

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3. Stability 
- Definition: The change in bias over time under consistent conditions. 
- Purpose: Ensures measurement consistency over time. 
- Key Points: 
   - Stability studies identify effects of environment, wear, or drift. 
   - Required even if calibration is performed. 

- Graph: Displays bias over time on a control chart. Deviations indicate instability.

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Precision (How Repeatable the Measurements Are) 
Precision is measured using GRR (Gage Repeatability & Reproducibility).

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4. GRR (Gage Repeatability & Reproducibility) 
- Definition: Total variation in a measurement system due to: 
   - Repeatability: Variation caused by the measuring equipment. 
   - Reproducibility: Variation caused by different operators (appraisers). 

- Purpose: Ensures measurements are consistent regardless of operator or tool. 
- Key Points: 
   - Repeatability = Equipment error. 
   - Reproducibility = Operator error. 

- Graph: Shows bell curves illustrating GRR spread compared to the reference value.

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Attribute Analysis (Qualitative Measurements) 
Attribute data focuses on categorization like OK/Not OK and includes:

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5. Miss Rate 
- Definition: Rate of missing defects (calling "Not OK" parts as "OK"). 
- Purpose: Measures failure to detect issues. 

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6. False Alarm 
- Definition: Rate of false alarms (calling "OK" parts as "Not OK"). 
- Purpose: Identifies unnecessary rejections caused by the system.

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7. Effectiveness 
- Definition: Proportion of correct measurements: 
   - "OK" parts as "OK" 
   - "Not OK" parts as "Not OK" 
- Purpose: Evaluates the overall accuracy of the attribute system.

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8. Kappa 
- Definition: Agreement of results between: 
   - Two appraisers. 
   - An appraiser and the reference value. 
- Purpose: Ensures consistency in classification results.

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Key Takeaways 

• Accuracy: Includes Bias, Linearity, and Stability.
• Precision: Measured through GRR (Repeatability and Reproducibility).
• Attribute Analysis: Includes Miss Rate, False Alarm, Effectiveness, and Kappa.
• MSA ensures reliable, consistent, and accurate measurement results for decision-making.