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Six Sigma Syllabus

LEAN Six Sigma


Define Phase

The Basics of Six Sigma

1.1.1 Meanings of Six Sigma
1.1.2 General History of Six Sigma & Continuous Improvement
1.1.3 Deliverables of a Lean Six Sigma Project
1.1.4 The Problem Solving Strategy Y = f(x)
1.1.5 Voice of the Customer, Business and Employee
1.1.6 Six Sigma Roles & Responsibilities

Selecting Lean Six Sigma Projects

1.3.1 Building a Business Case & Project Charter
1.3.2 Developing Project Metrics
1.3.3 Financial Evaluation & Benefits Capture

The Lean Enterprise

1.4.1 Understanding Lean
1.4.2 The History of Lean
1.4.3 Lean & Six Sigma
1.4.4 The Seven Elements of Waste
a. Overproduction, Correction, Inventory, Motion, Overprocessing, Conveyance, Waiting.
1.4.5 5S
a. Straighten, Shine, Standardize, Self-Discipline, Sort



Analyze Phase

Patterns of Variation

3.1.1 Multi-Vari Analysis
3.1.2 Classes of Distributions

Inferential Statistics

3.2.1 Understanding Inference
3.2.2 Sampling Techniques & Uses
3.2.3 Central Limit Theorem

Hypothesis Testing

3.3.1 General Concepts & Goals of Hypothesis Testing
3.3.2 Significance; Practical vs. Statistical
3.3.3 Risk; Alpha & Beta
3.3.4 Types of Hypothesis Test

Hypothesis Testing with Normal Data

3.4.1 1 & 2 sample t-tests
3.4.2 1 sample variance
3.4.3 One Way ANOVA
a. Including Tests of Equal Variance, Normality Testing and Sample Size calculation, performing tests and interpreting results.

Hypothesis Testing with Non-Normal Data

3.5.1 Mann-Whitney
3.5.2 Kruskal-Wallis
3.5.3 Mood’s Median
3.5.4 Friedman
3.5.5 1 Sample Sign
3.5.6 1 Sample Wilcoxon
3.5.7 One and Two Sample Proportion
3.5.8 Chi-Squared (Contingency Tables)
a. Including Tests of Equal Variance, Normality Testing and Sample Size calculation, performing tests and interpreting results.


Improve Phase

Lean Controls

5.1.1 Control Methods for 5S
5.1.2 Kanban
5.1.3 Poka-Yoke (Mistake Proofing)

Statistical Process Control (SPC)

5.2.1 Data Collection for SPC
5.2.2 I-MR Chart
5.2.3 Xbar-R Chart
5.2.4 U Chart
5.2.5 P Chart
5.2.6 NP Chart
5.2.7 Xbar-S Chart
5.2.8 CuSum Chart
5.2.9 EWMA Chart
5.2.10 Control Methods
5.2.11 Control Chart Anatomy
5.2.12 Subgroups, Impact of Variation, Frequency of Sampling
5.2.13 Center Line & Control Limit Calculations

Six Sigma Control Plans
5.3.1 Cost Benefit Analysis
5.3.2 Elements of the Control Plan
5.3.3 Elements of the Response Plan






Measure Phase

Process Definition

2.1.1 Cause & Effect / Fishbone Diagrams
2.1.2 Process Mapping, SIPOC, Value Stream Map
2.1.3 X-Y Diagram
2.1.4 Failure Modes & Effects Analysis (FMEA)

Six Sigma Statistics

2.2.1 Basic Statistics
2.2.2 Descriptive Statistics
2.2.3 Normal Distributions & Normality
2.2.4 Graphical Analysis

Measurement System Analysis

2.3.1 Precision & Accuracy
2.3.2 Bias, Linearity & Stability
2.3.3 Gage Repeatability & Reproducibility
2.3.4 Variable & Attribute MSA

Process Capability

2.4.1 Capability Analysis
2.4.2 Concept of Stability
2.4.3 Attribute & Discrete Capability
2.4.4 Monitoring Techniques

Improve Phase

Simple Linear Regression

4.1.1 Correlation
4.1.2 Regression Equations
4.1.3 Residuals Analysis

Multiple Regression Analysis

4.2.1 Non- Linear Regression
4.2.2 Multiple Linear Regression
4.2.3 Confidence & Prediction Intervals
4.2.4 Residuals Analysis
4.2.5 Data Transformation, Box Cox

Designed Experiments

4.3.1 Experiment Objectives
4.3.2 Experimental Methods
4.3.3 Experiment Design Considerations

Full Factorial Experiments

4.4.1 2k Full Factorial Designs
4.4.2 Linear & Quadratic Mathematical Models
4.4.3 Balanced & Orthogonal Designs
4.4.4 Fit, Diagnose Model and Center Points

Fractional Factorial Experiments

4.5.1 Designs
4.5.2 Confounding Effects
4.5.3 Experimental Resolution
































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