Advanced Statistical Process Control

Course Overview

This course builds on the fundamental SPC concepts and traditional charts learned in the Statistical Process Control course. More advanced charts that are necessary for handling modern production methods are covered in detail. This course also teaches participants how to handle non-Normal data. It is assumed that participants have taken Statistical Process Control (or equivalent).

Seminar Content

  1. Review of Traditional SPC
    • Normal & Non-Normal Distributions
    • Stability & Capability
    • Spec Limits & Control Limits
    • Definition of Quality
    • Quality Control vs. Process Control
  2. Sampling and Sample Size (Sensitivity)
    • Type I and Type II Errors
    • Sensitivity & Sample Size
  3. Two Potentially Different Processes
    • Two Measurements from a Single Unit
    • A Single Measurement on Two “Related” Units
    • Paired t Test
    • Xbar, Rb, Rw, and d Charts
  4. Multiple Potentially Different Processes
    • Multiple Measurements from a Single Unit
    • A Single Measurement on Multiple “Related” Units
    • Analysis of Variance (ANOVA)
    • Xbar, Rb, Rw, and d Charts
  5. Testing for Normality
    • Graphical Tests for Normality
    • Normal Probability Plots
    • Moments Tests
    • Other Tests
  6. SPC for Non-Normal Data
    • Pearson Curve Fitting
    • Box Cox Transformations
    • Distribution Fitting
  7. SPC for Trending Data
    • Charts for Trending Data
    • Simple Linear Regression
    • Coding Data to Account for Trends
  8. Other Charts for Individuals
    • Non-Normal Individuals
    • CUSUM Charts
    • EWMA Charts
  9. Attribute Charts
    • Review of Charts for Attribute Data
    • p, np, c, u charts
    • Standardized Charts for Varying Sample Sizes (standardized p chart and standardized u chart)