Master Lean Six Sigma Green Belt Level

Competences and hands-on approach to manage Projects.

The Lean Six Sigma Green Belt course is intended to train people capable of leading Lean Six Sigma projects, having the following skills and responsibilities:

  • Basic knowledge of Lean Six Sigma tools and techniques
  • Basic knowledge of software for statistical data management
  • Leadership role on small scale projects, supervised by a Lean Black Belt
  • Part-time commitment on projects



A highly customized Lean Six Sigma training program with a hands-on approach.

Training program details:

  • Online Welcome Assessment. This assessment is intended to assess the initial level of knowledge of Lean Six Sigma tools and techniques and thus to customize lessons accordingly
  • Training Sessions (11 modules – 8 training hours per module)
  • Certification:
    • Final Test: 100 multiple choice questions including theory and exercises
    • Project Work submission

Tutoring program details:

  • In-house and remote Lean Six Sigma Projects tutoring

Detailed Program

Introduction to Six Sigma

  • QM introduction: background – TQM – Lean – Six Sigma
  • Six Sigma introduction: DMAIC DFSS (DMADV)
  • Six Sigma introduction:  roadmaps, roles and key players



  • From the Voice of the Customer to the project
  • Project Charter: appropriate and effective project documentation
  • Introduction to operative and economic metrics to measure the project
  • Six Sigma metrics: from % to PPM and DPMO
  • Processes mapping: VSM, SIPOC and technological diagram
  • Stratification and clustering: the right approach to deal with data
  • Pareto analysis and Juran approach for problem setting

Presentation and discussion of a real case study of Project Charter implementation in a paper mill organization *



  • How to plan an effective data gathering: Data Collection Plan
  • What characteristic to monitor
  • Statistical basics and its industrial use
  • Statistical dispersion and central tendency measurement
  • Effective graphical data presentation: histograms, scatterplots, Boxplot, runcharts
  • Normal distribution and its industrial utilization
  • Process capability: Cp, Cpk, Pp, Ppk
  • Process performance KPIs
  • Confidence interval
  • Sampling and sample sizing
  • Measurement System Analysis: the tolerancing problem in measurement processes
  • Gauge R&R and the importance of reliability for measures in KPIs dashboards

Presentation and discussion of a real case study about Capability Problem *



  • The Qualitative and Quantitative approach to support decision
  • C&E Analysis with Ishikawa and C&E Matrix
  • Root causes: 5Ws, 4Ws+H
  • Hypothesis Tests and their appropriate use
  • Contingency Table (crosstab)
  • Correlation and regression analysis

Presentation and discussion of a real case study about problem setting and analysis tools and techniques DoE*



  • How to set solutions for improvement: DoE basics
  • DoE implementation to experimental planning for industrial use
  • Developing and interpreting full-factorial DoE
  • Innovative solutions generation: convergent and divergent thinking introduction
  • Operative methodologies to rank and select solutions

Presentation and discussion of a real case study about DoE implementation in testing *



  • Control phase: basics and introductive approach to a correct and knowledge-based use
  • Control Charts fundamentals
  • Control and reactions plans
  • Statistical Process Control basics
  • Control Charts: introduction to variable data and attributes and their features
  • Construction of control charts for continuous data

Presentation and discussion of a real case study about : Control Charts and Reaction Plan *

* Case Studies are introduced and discussed during the training sessions


Certification requirements

In order to earn the certification is required to:
1. Attend at least 80% of all scheduled training sessions
3. Pass the Final Online Test
2. Submit a final Project Work

Request for information

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