Introduction: What is Measurement Study? When and why use MSA? Application of MSA. Sources of variation. Impact of measurement errors. Causes of measurement variation.
Components of MSA: Resolution or Discrimination, Measurement Error, Bias, Gage R&R, Linearity, Stability, Calibration Plot, and Attribute R&R.
Resolution or Discrimination: Meaning and calculation of resolution with example.
Measurement Error: Measurement System Error; Repeatability and Reproducibility. Measurement Error in mathematical terms. Measurement error categories; Accuracy and Precision. Assessing measurement data.
Bias: Definition of Bias. Bias as % of Tolerance. Example problem to calculate Bias.
Gage R&R: Repeatability (EV), Reproducibility (AV). Calculation of Gage R&R. Total Process Variation. Number of Distinct Data Categories (NDC). Measurement Capability Indices (MCI). Gage R&R w.r.t. Total variation, Gage R&R w.r.t. Tolerance. Case study; Gage R&R, Interpretation of Repeatability and Reproducibility Charts.
Linearity: Definition of linearity. Concept of linear equation. Components of linearity; Bias, Equation of linearity, %Linearity, Point of zero bias, Coefficient of determination. Linearity chart in excel. Example problem. Interpretation of Linearity chart.
Stability: Definition of stability. Stability mean chart and range chart. Example problem and interpretation of stability chart.
Calibration plot: Meaning and understanding of calibration plot. Example problem and interpretation of calibration plot.
Attribute R&R: Interpretation of repeatability and reproducibility of attribute data.