Why Do Six Sigma
- Definition and graphical view of Six Sigma.
- Comparisons between typical TQM and Six Sigma Programs.
- Origins and Success Stories.
How to Deploy Six Sigma
- Leadership responsibilities
- Description of the roles and responsibilities
- Resource allocation
- Data driven decision making
- Organizational metrics and dashboards
Six Sigma Projects
- Project Focus
- Selecting Projects
- Overview of DMAIC methodology
- Project Reporting
DEFINE: Project Definition
- Tasks.
- Project Charters.
- Work Breakdown Structure.
- Pareto Diagrams.
- Process Maps.
- SIPOC.
- Reporting.
DEFINE: Metrics & DeliverablesCTC, CTQ, CTS Parameters
- CTx Flow-down Model (Big Y's, Little y's)
- Measurement & Feedback
- Throughput Yield, DPMO, Sigma Level Calculations
- Process Cycle Efficiency, Lead Time, Velocity, OEE Calculations.
DEFINE: Project Financials
- Quality Cost Classifications.
- Quantifying Project Benefits
- EBIT, NPV, IRR Calculations.
DEFINE: Project Scheduling
- Critical Path Analysis / Activity Network Diagram.
- PERT Analysis.
- GANNT Chart.
DEFINE: Change Management and Six Sigma Teams
- Problems with Change
- Achieving Buy-In
- Team Formation, Rules & Responsibilities
- Consensus Building
MEASURE: Tools
- Measure Stage Objectives
- Process Definition (Flowcharts, Process Maps)
- Metric Definition.
- Enumerative vs. Analytic Statistics.
- Process Variation (Deming's Red Bead) Benefits of Control Charts.
- Requirements vs. Control (Tampering)
- Control Chart as Process Baseline Tool.
MEASURE: Distributions
- General Probability Rules.
- Binomial Distribution: Uses, Assumptions, Excel & Minitab.
- Hyper geometric Distribution: Uses, Assumptions, Excel & Minitab.
- Poisson distribution: Uses, Assumptions, Excel & Minitab.
- Normal Distribution: Uses, Assumptions, Excel & Minitab.
- LogNormal Distribution: Uses, Assumptions, Excel & Minitab.
- Exponential Distribution: Uses, Assumptions, Excel & Minitab.
- Weibull Distribution: Uses, Assumptions, Excel & Minitab.
- Probability Plots
- Goodness of Fit Tests
MEASURE: X-Bar Charts
- Uses / Assumptions
- Construction & Calculations.
- Rational Subgroups & Sampling Considerations.
- Interpretation.
- Run Test Rules.
MEASURE: Individuals Data
- Uses.
- Construction & Calculations.
- Assumptions & Sampling Considerations.
- Interpretation. Overview of Other Individuals Charts: Run Charts; Moving Average Charts; EWMA Charts.
- MEASURE: Process Capability
- Histograms.
- Capability & Performance Indices (Interpretation; Estimating Error)
MEASURE: Attribute Charts
- Uses.
- Selection.
- Construction & Calculations.
- Sampling Considerations.
- MEASURE: Short Run SPC
- Uses.
- Calculations.
- Nominals chart.
- Stabilized Chart.
MEASURE: Measurement Systems Analysis
- Stability Studies.
- Linearity Analysis.
- R&R Analysis.
- Range Method Calculations.
- Interpretation.
- Using Control Charts.
- Destructive Tests.
- ANOVA Method.
ANALYZE: Value Stream Analysis
- Definition of Waste.
- Analyzing Process for NVA using VSA.
- Analyzing Lead Time and Velocity
ANALYZE: Sources of Variation
- Multi-vari Plots.
- Confidence Intervals on Means & Percents.
- Hypothesis Testing Method, Assumptions and Uses.
- Hypothesis Tests on Mean, Two Sample Means, Paired Samples.
- Hypothesis Tests on Variance, Two Sample Variances.
- Contingency tables.
- Power & Sample Size Considerations.
- Non-parametric Tests.
ANALYZE: ANOVA
- Assumptions & Bartlett’s Equality of Variance Test.
- One-way ANOVA.
- Two-way ANOVA.
- Multi-factor ANOVA.
- Tukey’s HSD Test.
ANALYZE: Regression Analysis
- Cause & Effect Diagrams.
- Scatter Diagrams.
- Correlation, Stratification.
- Linear Model. Interpreting the ANOVA Table.
- Confidence & Prediction Limits.
- Residuals Analysis.
- Overview of Multiple Regression Tools
- DOE vs. Traditional Experiments & Data Mining
ANALYZE: Multiple Regression
- Multivariate Models.
- Interaction Plots.
- Interpreting ANOVA Tables.
- Model Considerations.
- Stepwise Regression.
- Residuals Analysis.
ANALYZE: DOE Introduction
- Terminology
- DOE vs. Traditional Experiments
- DOE vs. Historical Data
- Design Planning.
- Selecting Responses.
- Selecting Factors and Levels.
- Complete Factorials.
- Fractional Factorials.
- Aliasing.
- Screening Designs.
ANALYZE: DOE Analysis Fundamentals
- Estimating Effects and Coefficients. Significance Plots.
- Estimating Error & Lack of Fit.
- Extending Designs.
- Power of Design.
- Tests for Surface Curvature.
ANALYZE: Design Selection
- Desirable Designs.
- Performance: Balance, Orthogonality, Resolution.
- Other Design Models.
- Saturated Designs.
- Placket Burman Designs.
- Johns 3/4 Designs.
- Central Composite Designs.
- Box Behnken Designs.
ANALYZE: Transforms
- Need for Transformations.
- Non-Constant Variance.
- Box-Cox Transforms.
- Calculated Parameters.
- Taguchi Signal to Noise Ratios.
IMPROVE: Tools
- Improve Stage Objectives.
- Tools to Prioritize Improvement Opportunities.
- Defining New Process Flow.
- Lean Tools to reduce NVA and Achieve Flow, including 5S.
- Defining New Process Levels.
- Improving Lead Times and Setup Times.
- Tools to Define & Mitigate Failure Modes.
IMPROVE: Response Surface Analysis
- Objectives.
- Applications.
- Sequential Technique.
- Steepest Ascent.
IMPROVE: Ridge Analysis
- Graphical Method.
- Overlaid Contours.
- Desirability Function.
IMPROVE: Simulations
- Applications.
- Examples.
- Applying Probabilistic Estimates.
IMPROVE: Evolutionary Operation
- Methodology.
- Example.
- Risks & Advantages.
- CONTROL: Tools
- Control Stage Objectives.
- Control Plans. Training.
- Measuring Improvement.
CONTROL: Serial Correlation
- Applications.
- Estimating Autocorrelation.
- Interpreting Autocorrelation.
- Batch Control Charts.
Design for Six Sigma Overview
- Methodology.
- Tools for DFSS.
- System, Parameter and Tolerance Designs.
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