IASSC Six Sigma Green & Black Belt Certification Bundle

About this course

This certification course will prepare you to successfully lead and execute Lean Six Sigma projects, perform Six Sigma analysis, and use the D.M.A.I.C (Define Measure Analyze Improve Control) methodology.

It is comprised of professionally narrated e-Learning modules, interactive quizzes, tests and exams. All delivered through a system that you will have access to 24 hours a day, 7 days a week.


At the end of this course, you will be able to:

Become a key stakeholder in leading, and implementing lean six sigma projects in your organization
Understand Six Sigma and DMAIC Methodology
Describe how to identify an improvement project in the Define phase
Explain how to measure process and product in the Measure phase
Perform data analysis and hypothesis testing in the Analyze phase
Identify the possible improvement actions for the performance of variations in the Improve phase
Define efficient operating levels for inputs and outputs in the Control phase
Identify the voice of customers, their requirement & needs
Understand their role in the success deployment
Understand how to develop a strategy for Six Sigma approach
Apply the DMAIC process to business issues


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 Green and/or Black Belt certified
Course can be completed in 30-60 days per belt
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