IASSC Lean Six Sigma Black Belt Training and Exam Prep course

Who is this course aimed at?

Lean Six Sigma Black Belt is most beneficial for organizations that encourage employees to take up Quality projects and ensure efficiency in all business/industry processes. This certification is most suited for:

Quality and Process Managers, System Managers, Analysts, Auditors, Engineers and Executives who need to have a better understanding of Six Sigma and the application of Six Sigma in process/quality improvements.
Production Managers, Production Supervisors, and Customer Service Managers
Persons wanting an initial introduction to Six Sigma thinking and techniques
Consultants who want to incorporate Six Sigma Black Belt into their service offerings
Professionals working in the support functions like Finance, Purchase, Marketing, Training, Recruitment, Operations, IT-Support, Travel.
Six Sigma Green Belts looking to progress to Black Belt


Key Points:

Provided by an IASSC fully Accredited Training Organisation (ATO): Hudson
Upon successful completion of the final exam (exam fee not included), you will receive a certification from the IASSC confirming you are fully Six Sigma Black Belt certified
Course can be completed in 30-60 days
12 months access to course material


What does this course cover?

OVERVIEW

1.0 DEFINE
1.1 Six Sigma Overview
1.1.1 What is Six Sigma
1.1.2 Six Sigma History
1.1.3 Six Sigma Approach Y = f(x)
1.1.4 Six Sigma Methodology
1.1.5 Roles & Responsibilities
1.2 The Fundamentals of Six Sigma
1.2.1 Defining a Process
1.2.2 VOC & CTQ’s
1.2.3 QFD
1.2.4 Cost of Poor Quality (COPQ)
1.2.5 Pareto Analysis (80:20 rule)
1.3 Lean Six Sigma Projects
1.3.1 Six Sigma Metrics
1.3.2 Business Case & Charter
1.3.3 Project Team Selection
1.3.4 Project Risk Management
1.3.5 Project Planning
1.4 Lean Fundamentals
1.4.1 Lean & Six Sigma
1.4.2 History of Lean
1.4.3 The Seven Deadly Muda
1.4.4 Five-S (5S)


2.0 MEASURE
2.1 Process Definition
2.1.1 Cause & Effect Diagrams
2.1.2 Cause & Effects Matrix
2.1.3 Process Mapping
2.1.4 FMEA
2.1.5 Theory of Constraints
2.2 Six Sigma Statistics
2.2.1 Basic Statistics
2.2.2 Descriptive Statistics
2.2.3 Distributions & Normality
2.2.4 Graphical Analysis
2.3 Measurement System Analysis
2.3.1 Precision & Accuracy
2.3.2 Bias, Linearity & Stability
2.3.3 Gage R&R
2.3.4 Variable & Attribute MSA
2.4 Process Capability
2.4.1 Capability Analysis
2.4.2 Concept of Stability
2.4.3 Attribute & Discrete Capability
2.4.4 Monitoring Techniques


3.0 ANALYZE
3.1 Patterns of Variation
3.1.1 Multi-Vari Analysis
3.1.2 Classes of Distributions
3.2 Inferential Statistics
3.2.1 Understanding Inference
3.2.2 Sampling Techniques & Uses
3.2.3 Sample Size
3.2.4 Central Limit Theorem
3.3 Hypothesis Testing
3.3.1 Goals of Hypothesis Testing
3.3.2 Statistical Significance
3.3.3 Risk; Alpha & Beta
3.3.4 Types of Hypothesis Test
3.4 Hypothesis Testing: Normal
3.4.1 1 & 2 sample t-tests
3.4.2 1 sample variance
3.4.3 One Way ANOVA
3.5 Hypothesis Testing: Non-Normal
3.5.1 Mann-Whitney & Mood’s Median
3.5.2 Kruskal-Wallis
3.5.3 Moods Median
3.5.4 Friedman
3.5.5 1 Sample Sign
3.5.6 1 Sample Wilcoxon
3.5.7 1 and 2 Sample Proportion
3.5.8 Chi-Squared
3.5.9 Test of Equal Variances


4.0 IMPROVE
4.1 Simple Linear Regression
4.1.1 Correlation
4.1.2 X-Y Diagram
4.1.3 Regression Equations
4.1.4 Residuals Analysis
4.2 Multiple Regression Analysis
4.2.1 Non-Linear Regression
4.2.2 Multiple Linear Regression
4.2.3 Confidence Intervals
4.2.4 Residuals Analysis
4.2.5 Data Transformation, Box Cox
4.2.6 Stepwise Regression
4.2.7 Logistic Regression
4.3 Designed Experiments
4.3.1 Experiment Objectives
4.3.2 Experimental Methods
4.3.3 DOE Design Considerations
4.4 Full Factorial Experiments
4.4.1 2k Full Factorial Designs
4.4.2 Linear & Quadratic Models
4.4.3 Balanced & Orthogonal Designs
4.4.4 Fit, Model & Center Points
4.5 Fractional Factorial Experiments
4.5.1 Designs
4.5.2 Confounding Effects
4.5.3 Experimental Resolution


5.0 CONTROL
5.1 Lean Controls
5.1.1 Control Methods for 5S
5.1.2 Kanban
5.1.3 Poka-Yoke (Mistake Proofing)
5.2 Statistical Process Control
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 X-S chart
5.2.8 CumSum Chart
5.2.9 EWMA Chart
5.2.10 Control Methods
5.2.11 Control Chart Anatomy
5.2.12 Subgroups/Variation/Sampling
5.2.13 Center Line & Control Limits
5.3 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