Six Sigma Black Belt GES 215 » 200 hours

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  1. Why Do Six Sigma
    1. Definition and Graphical View of Six Sigma
      1. Overview of Business Applications
      2. Example Sigma Levels
      3. Introduction to DPMO and Cost as Metrics
    2. Comparisons Between Typical TQM and Six Sigma Programs
    3. Origins and Success Stories
  2. How to Deploy Six Sigma
    1. Leadership Responsibilities
    2. Description of the Roles and Responsibilities
    3. Resource Allocation
    4. Data-driven Decision Making
    5. Organizational Metrics and Dashboards
  3. Six Sigma Projects
    1. Project Focus
    2. Selecting Projects
    3. Overview of DMAIC Methodology
    4. Project Reporting
  4. Incorporating Voice of the Customer
    1. Goal Posts vs. Kano
    2. Customer Focus and the Leadership Role
    3. Overview of QFD
    4. Customer Data
    5. Big Y's, Little Y's
  5. DEFINE: Project Definition
    1. Tasks
    2. Work Breakdown Structure
    3. Pareto Diagrams
    4. Process Maps
    5. Matrix Diagrams
    6. Project Charters
    7. Reporting
  6. DEFINE: Project Financials
    1. Quality Cost Classifications
    2. Quantifying Project Benefits
    3. Calculations
  7. DEFINE: Goals and Metrics
    1. CTC, CTQ, CTS Parameters
    2. CTx Flow-down Model (Big Y's, Little Y's)
    3. Measurement & Feedback
    4. Calculating Sigma Levels
  8. DEFINE: Project Scheduling
    1. Activity Network Diagram
    2. PERT Analysis
    3. GANNT Chart
  9. DEFINE: Change Management/Teams
    1. Problems With Change
    2. Achieving Buy-in
    3. Team Formation, Rules, and Responsibilities
      1. Stages of Team Development
      2. Overcoming Problems
    4. Consensus Building
      1. Affinity Diagram
      2. Nominal Group Technique
      3. Prioritization Matrix
  10. MEASURE: Tools
    1. Measure Stage Objectives
    2. Flowcharts
    3. Process Maps
    4. SIPOC
    5. Box-Whisker Plots
    6. Cause and Effect Diagrams
    7. Check Sheets
    8. Interrelationship Digraph
    9. Stem and Leaf Plots
  11. MEASURE: Establishing Process Baseline
    1. Enumerative vs. Analytic Statistics
    2. Process Variation
      1. Deming's Red Bead
    3. Benefits of Control Charts
    4. Requirements vs. Control
      1. Tampering
    5. Control Chart Interpretation
      1. Relative to Process Baseline Estimates
  12. MEASURE: X-Bar Charts
    1. Uses
    2. Construction and Calculations
    3. Assumptions
    4. Rational Subgroups
    5. Sampling Considerations
    6. Interpretation
      1. Run Test Rules
  13. MEASURE: Individuals Data
    1. Uses
    2. Construction and Calculations
    3. Assumptions
    4. Sampling Considerations
    5. Interpretation
    6. Overview of Other Individuals Charts
      1. Run Charts
      2. Moving Average Charts
      3. EWMA Charts
  14. MEASURE: Process Capability
    1. Histograms
    2. Probability Plots
    3. Goodness of Fit Tests
    4. Capability and Performance Indices
      1. Relative to Process Control
      2. Interpretation
      3. Estimating Error
  15. MEASURE: Attribute Charts
    1. Uses
    2. Selection
    3. Construction and Calculations
    4. Sampling Considerations
  16. MEASURE: Short Run SPC
    1. Uses
    2. Calculations
      1. Nominals Chart
      2. Stabilized Chart
  17. MEASURE: Measurement Systems Analysis
    1. Stability Studies
    2. Linearity Analysis
    3. R&R Analysis
      1. Range Method Calculations
      2. Interpretation
      3. Using Control Charts
      4. Destructive Tests
      5. ANOVA Method
  18. ANALYZE: Lean Thinking
    1. Definition of Waste
    2. Analyzing Process for NVA
      1. Cycle Efficiencies
      2. Lead Time and Velocity
      3. Methods to Increase Velocity
        1. Standardization
        2. Optimization
        3. Spaghetti Diagrams
        4. 5S
        5. Level Loading
        6. Flow
        7. Setup Reductions
    3. ANALYZE: Sources of Variation
      1. Multi-vari Plots
      2. Confidence Intervals on Mean
      3. Confidence Intervals on Percent
      4. Hypothesis Test on Mean
      5. Hypothesis Test on Mean of Two Samples
      6. Power and Sample Size
      7. Contingency Tables
      8. Non-parametric Tests
    4. ANALYZE: Regression Analysis
      1. Scatter Diagrams
      2. Linear Model
      3. Interpreting the ANOVA Table
      4. Confidence and Prediction Limits
      5. Residuals Analysis
      6. Overview of Multiple Regression Tools
        1. DOE vs. Traditional Experiments and Data Mining
    5. ANALYZE: Multiple Regression
      1. Multivariate Models
      2. Interaction Plots
      3. Interpreting ANOVA Tables
      4. Model Considerations
      5. Stepwise Regression
      6. Residuals Analysis
    6. ANALYZE: DOE Introduction
      1. Terminology
      2. DOE vs. Traditional Experiments
      3. DOE vs. Historical Data
      4. Design Planning
      5. Design Specification
        1. Selecting Responses
        2. Selecting Factors and Levels
      6. Complete Factorials
      7. Fractional Factorials
        1. Aliasing
        2. Screening Designs
    7. ANALYZE: DOE Analysis Fundamentals
      1. Estimating Effects and Coefficients
      2. Significance Plots
      3. Estimating Error
      4. Extending Designs
      5. Power of Design
      6. Lack of Fit
      7. Tests for Surface Curvature
    8. ANALYZE: Design Selection
      1. Desirable Designs
      2. Performance
        1. Balance
        2. Orthogonality
        3. Resolution
      3. Other Design Models
        1. Saturated Designs
        2. Plackett Burman Designs
        3. Johns 3/4 Designs
        4. Central Composite Designs
        5. Box Behnken Designs
        6. Taguchi Designs (Mention)
    9. ANALYZE: Transforms
      1. Need for Transformations
      2. Non-constant Variance
      3. Box-Cox Transforms
      4. Calculated Parameters
      5. Taguchi Signal to Noise Ratios
    10. IMPROVE: Tools
      1. Improve Stage Objectives
      2. Tools to Prioritize Improvement Opportunities
      3. Tools to Define New Process Flow
        1. Lean Tools to Reduce NVA and Achieve Flow
      4. Tools to Define and Mitigate Failure Modes
        1. PDPC
        2. FMECA
        3. Preventing Failures
      5. Reference to Tools for Defining New Process Levels
    11. IMPROVE: Response Surface Analysis
      1. Objectives
      2. Applications
      3. Sequential Technique
      4. Steepest Ascent
    12. IMPROVE: Ridge Analysis
      1. Graphical Method
      2. Analytical Method
      3. Overlaid Contours
      4. Desirability Function
    13. IMPROVE: Simulations
      1. Applications
      2. Examples
      3. Applying Probabilistic Estimates
    14. IMPROVE: Evolutionary Operation
      1. Methodology
      2. Example
      3. Risks and Advantages
    15. CONTROL: Tools
      1. Control Stage Objectives
      2. Control Plans
      3. Training
      4. Measuring Improvement
    16. CONTROL: Serial Correlation
      1. Applications
      2. Estimating Autocorrelation
      3. Interpreting Autocorrelation
      4. Batch Control Charts
    17. Design for Six Sigma Overview
      1. Methodology
      2. Tools for DFSS
      3. System, Parameter, and Tolerance Designs

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