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COURSE OVERVIEW - What's included
Prices on application inclusive of all software & textbooks used on the course.

LEAN SIX SIGMA GREEN BELT
LEAN SIX SIGMA BLACK BELT

Design for Six Sigma Greenbelt (DFSS)

DESIGN FOR SIX SIGMA Foundations - Week 1
DESIGN FOR SIX SIGMA Capstones- Week 2

LEAN SIX SIGMA GREEN BELT
Training materials: Texts: Knowledge Based Management, Basic Statistics: Tools for Continuous Improvement, Lean Six Sigma: A Tools Guide; Software: SPC XL; Knowledge Notebook, Lean Six Sigma Green Belt student participant guide.

Course agenda:
Module 1 ~ Lean Six Sigma... The Journey Begins
Module 2 ~ Lean Six Sigma Fundamentals
Module 3 ~ Defining the Project and Managing Change
Module 4 ~ Understanding the Voice of the Customer (VOC) and Defining a Process
Module 5 ~ Measure ... Making Sense Out of Data Using Graphical & Measurement Tools
Module 6 ~ Measurement System Analysis
Module 7 ~ Analyzing the Causes of Poor Performance
Module 8 ~ Techniques for Narrowing the Focus
Module 9 ~ Drawing Conclusions from Sampled Data
Module 10 ~ Improving the Process and Work Flow
Module 11 ~ Controlling the Process Performance/Realizing and Holding the Gains
Module 12 ~ DMAIC Summary -- Putting It All Together
Module 13 ~ References, Glossary of Terms, Course Evaluations

LEAN SIX SIGMA BLACK BELT
Training materials: Texts: Knowledge Based Management, Basic Statistics: Tools for Continuous Improvement, Understanding Industrial Designed Experiments, Lean Six Sigma: A Tools Guide; Software: SPC XL, DOE KISS, DOE PRO, Simware; Knowledge Notebook, Black Belt student participant guide.

Course agenda:
Module 1 ~ Lean Six Sigma... The Journey Begins
Module 2 ~ Lean Six Sigma Fundamentals
Module 3 ~ Defining the Project and Managing Change
Module 4 ~ Understanding the Voice of the Customer (VOC) and Defining a Process
Module 5 ~ Measure ... Making Sense Out of Data Using Graphical & Measurement Tools
Module 6 ~ Measurement System Analysis
Module 7 ~ Analyzing the Causes of Poor Performance
Module 8 ~ Techniques for Narrowing the Focus
Module 9 ~ Drawing Conclusions from Sampled Data
Module 10 ~ Improving the Process and Work Flow
Module 11 ~ Controlling the Process Performance/Realizing and Holding the Gains
Module 12 ~ DMAIC Summary -- Putting It All Together
Module 13 ~ References, Glossary of Terms, Course Evaluations
Module 14 ~ Review of DMAIC Tools and Techniques
Module 15 ~ Additional Lean Tools to Define and Measure
Module 16 ~ Analyze Data Using Probability Distributions
Module 17 ~ Regression Modeling to Analyze and Improve
Module 18 ~ Introduction to the Use of Design of Experiments (DOE) to Analyze and Improve
Module 19 ~ Two-Level Designs
Module 20 ~ Three-Level Designs
Module 21 ~ Rules of Thumb and DOE Design Selection
Module 22 ~ Quick Review of DMAIC and DOE
Module 23 ~ Additional Lean Improvement Tools
Module 24 ~ Additional Hypothesis Tests to Analyze and Improve
Module 25 ~ DOE Diagnostics and Assessments
Module 26 ~ Advanced DOE Analysis Techniques and Designs
Module 27 ~ Historical Data Analysis
Module 28 ~ Lean Six Sigma Mini-Project
Module 29 ~ Advanced Black Belt Topics and Training
Module 30 ~ References, Glossary of Terms, and Course Evaluation Forms

DESIGN FOR SIX SIGMA GREENBELT (DFSS)

DESIGN FOR SIX SIGMA Foundations - Week 1
Training materials: Texts: Knowledge Based Management; Lean Six Sigma: A Tools Guide; Basic Statistics: Tools for Continuous Improvement; Understanding Industrial Designed Experiments; Software: SPC XL, DOE PRO; Design for Six Sigma Foundations student participant guide.

Course agenda:

Introduction to Design for Six Sigma (DFSS)
• The What and Why of Design for Six Sigma
• Design for Six Sigma Master Strategy: IDOV
• DFSS Studies and Projects
• Key Players and Roles
• Course Philosophy and Instructional Approach

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
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DESIGN FOR SIX SIGMA Capstone - Week 2
Training materials: Texts: Knowledge Based Management, Lean Six Sigma: A Tools Guide, Basic Statistics: Tools for Continuous Improvement, Understanding Industrial Designed Experiments; Software: SPC XL, DOE PRO, DFSS Master, SimWare Pro

Course agenda:

Introduction to Design for Six Sigma (DFSS)
• Comparing IDOV and DMAIC
• The DFSS Opportunity
• DFSS projects and studies
• The Identify, Design, Optimize, Validate (IDOV) Methodology
• Quantifying Savings and Benefits

Keeping Score
• Keeping Score using the DFSS Scorecard
• Scorecard Elements and Construction
• Parts
• Process
• Performance
• Software
• Methods for Computing DPU
• Hands-on practice completing a DFSS Scorecard using DFSS Master Software

Voice of the Customer
• The Identify phase of IDOV
• Determining Customer Wants and Needs
• Survey Statistics
• Identifying Critical to Customer Requirements
• Prioritizing Customer Requirements
• Introduction to Quality Function Deployment (QFD) and the House of Quality
• Hands-on Practice Completing House of Quality #1 to identify Measurable CTCs (critical to customer measures) Pugh Concept Generation and Selection, Systems Engineering, and Requirements Flowdown

• The Design phase of IDOV
• Assigning Specs and Formulating Design Concepts
• Overview of Triz and Axiomatic Design
• Comparing Alternate Design Concepts using Pugh Concept Selection
• Risk Analysis and Management
• Building House of Quality #2

The Transfer Function
• Importance of Transfer Functions for IDOV
• Methods for Obtaining Transfer Functions

Design for Robust Performance
• Concept of Deterministic vs. Probabilistic
• Expected Value Analysis (EVA) for Quantifying the Distribution of the Output
• Comparing Methods and Strategies for EVA
• Root Sum Square (RSS)
• Using Partial Derivatives
• Worst Case Analysis
• Monte Carlo Simulation
• Using DFSS Master for EVA Analysis
• Adding Noise to EVA
• Working with Normal and Non-Normal Output Distributions
• Robust Design: Finding Optimal Mean Settings for the Inputs to Minimize Variation in an Output
• Hands-on Robust Design experiment using the Statapult®
• Computer Based Robust Design (Parameter Design) using DFSS Master Software
• Robust Design Exercises using SimWare Pro Software

Tolerance Allocation
• Quantifying the Sensitivity of the Output DPM to Changes in the Input Variable’s Standard Deviation
• Tolerance Allocation Examples and Exercises
• Setting Tolerances
• Methods to Reduce the Standard Deviation of Inputs

Design for X-ability
• DFX Concepts – beyond just designing for performance
• Design for Manufacturability vs. Design for Performance
• Introduction to Design for Reliability (DFR)
• Mistake Proofing and Error Proofing

Product Capability Prediction
• Updating the DFSS Scorecard and Making Predictions
• Items to Consider for High DPU Elements

Test and Validate
• Sensitivity Analysis
• Comparing Predicted Capability with Actual Performance
• Gap Analysis
• Control Plans

Stat-a-Copter Design Exercise
• Capstone Exercise: Hands-on practice with the IDOV process
• Teams Design a Product to Meet the Customer Needs, using the IDOV process, complete with Optimization and Ultimately Limited Production and testing of Their design to Validate Performance

References and Course Evaluation Forms

TADSAM LTD - Danuta Kurucz, UK Associate Tel: 07921 182365 e-mail danuta@tadsam.co.uk