Advanced Six Sigma Tools

Advanced Six Sigma Tools

A Module of Master Black Belt Certification Programme


Course Overview

Six Sigma is a widely used methodology for measuring and improving an organization’s operational performance through a rigorous analysis of its practices and systems. The Six Sigma projects deliver through the application of well-defined set of statistical tools and process improvement techniques.

A company committing itself to a Six Sigma project must put in place an intensive training program for key executives and staff. In turn, these people learn to organize and effectively lead the deployment of the project, and to implement and use statistical tools and analytical techniques in their business-improvement efforts. This course is aimed at introducing various advanced Six Sigma tools as well as providing the knowledge on applying the appropriate techniques to tackle the problems. Such tools and methods include the advanced level of DOE, SPC, Capability Analysis and Regression Analysis. In-depth knowledge in deploying those Six Sigma tools will be discussed.

Who should attend?

1. First and second level team leaders and managers.
2. Quality and process improvement professionals.
3. Those interested in becoming Six Sigma professionals.

Course Outline

2.0 Review of Hypothesis Testing and Regression Analysis

2.1 Advanced DOE

2.1.1 Review of DOE Methods
2.1.2 Response Surface Design Central Composite and Box-Behnken Designs Sequential Experimentation Optimization Steepest Ascent Method Multiple Response

2.1.3 Trebuchet Experiment
2.1.4 Mixture Designs

2.2 Advance SPC

2.2.1 Overview of SPC
2.2.2 Cusum Chart
2.2.3 EWMA Chart
2.2.4 Cumulative Count Chart
2.2.5 Multivariate Chart
2.2.6 Pre-Control Chart
2.2.7 Cases and examples

2.3 Advanced Capability Analysis

2.3.1 Capability Analysis for Weibull data
2.3.2 Capability Analysis for Poisson data
2.3.3 Capability Analysis for Binomial data

2.4 Advance Regression Analysis

2.4.1 Stepwise Method
2.4.2 Logistic Regression

2.5 Forecasting Techniques

2.5.1 Time Series Analysis
2.5.2 Moving Average Methods
2.5.2 Exponential Smoothing Methods
2.5.4 Autocorrelation
2.5.5 Seasonal Analysis

2.6 Simulation and Exercise



Participants who complete the course and pass the examination will be awarded a module certificate.


CPD credits could be claimed:

30 credits


Course Fee

Please contact us for details.

Payment Method