Description
Lean and Six Sigma, both proven business improvement approaches, provide businesses with the ability to maximise customer, employee and shareholder value by minimising process variation and waste. This ten day course provides the experienced Green Belt with the necessary tools and techniques to manage improvement resources to deliver major projects. This hand-on learning experience develops both the delegate’s technical knowledge and personal skills. The course uses a blend of theory and practical exercises to ensure that participants have the confidence and capability to deliver more complex business improvement projects and transformations.
The examination, Lean Six Sigma Black Belt, is taken on the final day of the second week.
Prerequisites
Experienced Green Belts who want to enhance and apply their skills to larger more complex projects. Delegates must have completed Lean Six Sigma Practitioner Green Belt (Part 2) (LSSPGB2) or equivalent. Delegates should, ideally, have a project identified to complete post-training (this is required for certification).
Course Content
Define & Measure (Introduction to Statistical Analysis & Minitab)
Quality Functional Deployments & Kano Analysis
Statistical Concepts
Introduction to Minitab I & Data Manipulation
Introduction to Minitab II
Linking customer requirements to CTQs
Review the basic statistical concepts
Review the Minitab Environment
Using Minitab for Analysis
Measure (Measurement Systems Analysis)
Rational Subgrouping & Data Collection
Measurement Systems Analysis
Discrete Data Measurement & Application
Practical MSA
Stratify customers and determine what to measure
Minimise measurement error – Statapult & GRR
Inspection Efficiency and Card drop Exercise
Exercises in Minitab and more Statapult
Measure (Sample Size and Confidence Intervals)
Focussing the Problem, Cause and Effect and FMEA
Determining Appropriate Business Measures
Sample Size & Confidence Intervals
Methods to focus the problem
What to measure?
Measurement essentials
Analyse (Hypothesis Testing)
Hypothesis Testing Continuous Data
Hypothesis Testing Discrete Data
Hypothesis Testing Non-Normal Data