Six Sigma Fundamentals

• Basics of Six Sigma and its Key Principles
• Defining Processes Using IPO Diagrams
• Key Terminology (Distribution, Mean, Median, Standard Deviation, Cp, Cpk, sigma
   level, first pass yield, defects)
• PF/CE/CNX/SOP (the first line of defense against variation)

Measurement System Analysis

• Properties of a Good Measurement System
• Impact of Measurement System Variation
• How to Set Up, Conduct, and Perform a Measurement System Analysis
    - Variables Data
    - Attribute Data
• Interpretation of MSA Results and Metrics
    - Repeatability
    - Reproducibility
    - P/Tol ratio
    - Discrimination (resolution)
    - Effectiveness, Probability of False Rejects, Probability of False Accepts

Understanding Data Distributions and Their Applications

• Basic Concepts of Probability
• Fact that Probability is Often Not Intuitive
• Four Common Distributions and Their Application to Problem Solving
    - Binomial distribution
    - Poisson distribution
    - Exponential distribution
    - Normal distribution
• Using SPC XL for Calculating Probabilities

Introduction to Regression Analysis and Design of Experiments (DOE)

• What is Regression and What is it Used For?
• Terminology Involved in Simple Linear Regression
    - Intercept
    - Slope
    - Prediction Equation
    - Residual
    - R-Squared
• Use of SPC XL for Regression Analysis and Interpretation of Output
• Introduction to Design of Experiments (DOE)

Foundations of Design of Experiments (DOE)

• Purpose of Design of Experiments
• Experimentation Strategies
• Key DOE Terminology
• Introduction to Basic Graphical and Statistical Analysis of Data
• Interactions
• Introduction to DOE Pro Software and Hands-On Experimentation
  Using the Statapult® Catapult

Design and Analysis of Experiments

• Importance of Planning
• DOE 12 Step Process
• Review and Practice: Graphical and Statistical Analysis of Data
• Building Design Matrices
• Introduction to Fractional Factorial Designs
• DOE Examples
• Hands-on Practice with Modeling and Optimization using the Statapult®
• Reasons why Experiments May Fail to Confirm and How to Recover

Rules of Thumb for DOE

• Sample Size Guidelines for DOE
• Selecting the Best Design
• Determining Statistical Significance
• Interpreting R-square, Adjusted R-square, Tolerance and p-Values

Two Level Design Summary

• Use and Application of Two Level Designs
• Summary of Two Level Design Options
    - Full Factorial Designs
    - Fractional Factorial Designs
    - Screening Designs
• Awareness of Situations where Standard Design will Not Apply and KISS 
  Approaches for Dealing with these Situations
    - Nested Designs
    - Mixture Designs

Three Level Designs

• Qualitative vs. Quantitative Factors in DOE
• Use and Application of Three Level Designs
• Full Factorial Designs
• Screening Designs
• Box Behnken and Central Composite Designs
• Setting Up, Conducting, Analyzing, and Confirming a Quadratic Model Using the
  Statapult® Catapult

Variance Reduction Methods and Robust Design

• Strategies for Variance Reduction
• Robust Design and DOE
• Setting up and analyzing Robust Design experiments
• Reducing Transmitted Variation by Taking Advantage of Interactions and Non-
  Linearities

References, Glossary of Terms and Course Evaluation Forms