Lean Six Sigma Black Belt (Phase 2 & 3) – Body of Knowledge

Six Sigma Black Belt: Six Sigma Phase 2 & 3

To sit for AIGPE Black Belt Certification Exam, you are required to have completed 1) AIGPE Six Sigma Green Belt Training and 2) AIGPE Black Belt: Phase 0 & 1, Phase 2 & 3 and Phase 4 & 5 Training

3.0 Measure Phase
3.1 Identify What to Measure?

3.1.1 Difference between Efficiency Measures and Effective Measures

3.1.2 Cost of Poor Quality (COPQ)

3.1.3 8 Wastes

i. Defects

ii. Overproduction

iii. Waiting

iv. Non-Utilized Skills

v. Transportation

vi. Inventory

vii. Motion

viii. Excess Processing

3.1.4 What are Process Maps?

3.1.5 What are Value Stream Maps?

3.1.6 Takt Time

3.1.7 Types of Data – Continuous vs. Discrete

3.2 Plan and Collect Data

3.2.1 XY Matrix

3.2.2 Data Collection Plan

i. Performance Measures

ii. Operational Definition

iii. Stratification Factors

iv. Data Collection – Existing vs. New Data

v. How will the data be collected?

vi. Who will collect the data?

vii. When will the data be collected?

3.2.3 Sampling

i. Simple Random Sampling

ii. Stratified Random Sampling

iii. Systematic Sampling

iv. Cluster Sampling

v. Sample Size formula – Continuous Data

vi. Sample Size formula – Discrete Data

3.2.4 Measurement System Analysis (MSA)

i. Measurement System Analysis – Components of Variation

ii. Measurement System Errors

3.3 Determine Baseline Performance

3.3.1 What is Data Stability?

3.3.2 Run Charts

3.3.3 Normal Distribution

3.3.4 Central Limit Theorem

3.3.5 How to check Normality on Minitab?

3.3.6 Box-Cox Transformation

3.3.7 Yield

i. Classic Yield

ii. First Time Yield

iii. Rolled Throughput Yield (RTY)

3.4 Determine Baseline Performance – Discrete Data

3.4.1 What is Sigma Shift?

3.4.2 What are Defects?

3.4.3 What is a Unit?

3.4.5 What are Defectives?

3.4.6 What is Opportunity for Errors?

3.4.7 Calculate Process Sigma Multiple for Discrete Data

3.5 Determine Baseline Performance – Continuous Data

3.5.1 What are Specification Limits?

3.5.2 Calculate Process Sigma Multiple for Continuous Data using Minitab

4.0 Analyze Phase
4.1 Identify Performance Gaps

4.1.1 Brainstorming

4.1.2 Fishbone Diagram

4.1.3 5 Why Analysis

4.2 Ascertain Critical Root-Causes

4.2.1 Pareto Chart

4.2.2 Box Plot

4.2.3 Scatter Plot

4.2.4 Stem-and-Leaf Plot

4.2.5 Interval Plot

4.2.6 Fault Tree Analysis

4.2.7 Multi-Voting

4.2.8 Control-Impact Matrix

4.3 Hypothesis Testing

4.3.1 Introduction Hypothesis Testing

4.3.2 Hypothesis Testing – Mechanism and Steps

4.3.3 Identify the Hypothesis Test

4.3.4 How do you write the Null and Alternative Hypothesis

4.4 What is P-Value?

4.4.1 Confidence Level

4.4.2 Significance Level

4.4.3 P-Value

4.4.4 Infer the Results

4.5 Parametric Tests

4.5.1 1-Sample t test

4.5.2 2-Sample t test

4.5.3 Paired t test

4.5.4 One-Way ANOVA

4.5.5 One-Way ANOM (Analysis of Means)

4.6 Variance Tests

4.6.1 1-Variance test

4.6.2 2-Variance test

4.6.3 Test of Equal Variances

4.7 Non-Parametric Tests

4.7.1 1-Sample Sign test

4.7.2 Mann-Whitney test

4.7.3 Kruskal-Wallis test

4.7.4 Mood’s Median test

4.8 Correlation and Regression

4.8.1 What is Correlation?

4.8.2 Correlation vs. Causation

4.8.3 Correlation Coefficient

4.8.4 How to perform Correlation Analysis on Minitab?

4.8.5 How to perform Regression Analysis on Minitab?

4.8.6 Fitted Line Plot

4.9 Chi-Square and Proportion Tests | Hypothesis Testing Errors

4.9.1 Chi-Square test

4.9.2 1-Proportion test

4.9.3 2-Proportion test

4.9.4 Hypothesis Testing Errors

i. Type 1 or Alpha Error

ii. Type 2 or Beta Error

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