Black Belt Lean Six Sigma
Complex Problem Solving – Advanced Performance Level
Develop the skills to achieve advanced operational performance and solve highly complex problems using Lean, LSSx.0, DMAIC, and advanced statistical methods, including Design of Experiments.
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Next: 2 Nov 2026 · 10 dates
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10Daysor75Hours
Pricing
€4 990excl. VATOpen Enrollment Remote
€5 750excl. VATOpen Enrollment In-Person
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Small group sessions (maximum 12 participants).
Interactive learning approach with exercises, case studies, and serious games.
Complete training kit included (manuals and materials).
Session recordings available for remote participants for review and reinforcement.
Official LSSx.0 reference books included.
Recognized LSSx.0™ Lean Six Sigma Black Belt certification.
Target Audience
All sectors — industry and services
This Black Belt training course is designed for:
Process Analysts, Process Engineers, and continuous improvement professionals
Project Managers and consultants in organization, quality, or operational excellence
Professionals responsible for leading complex, cross-functional DMAIC improvement projects
Logistics Managers and Supply Chain Managers
Production Managers and Operations Managers
Quality Managers and Quality Engineers
Prerequisites: No specific prerequisites.
Learning Objectives
Lean Practitioner Module (Days 1-2)
Module 01
01
Understand the philosophy, tools, and principles of Lean Management
02
Assess operational performance, capacity, and resource losses
03
Create and analyze process maps based on field observations
04
Improve operational processes using Lean problem-solving methods
05
Develop performance management routines and lead improvement workshops
Six Sigma Yellow Belt Module (Days 3-4)
Module 02
01
Understand the foundations of Lean Six Sigma and the DMAIC framework
02
Identify the type of operational problem using the LSSx.0 typology and select the appropriate improvement trajectory
03
Define relevant quality criteria based on customer expectations
04
Identify root causes and evaluate potential improvement solutions
05
Lead a DMAIC project addressing a simple operational problem
Six Sigma Green Belt Module (Days 5-7)
Module 03
01
Define project metrics and structure robust data collection plans
02
Validate measurement systems to ensure reliable data
03
Identify and quantify root causes through statistical analysis
04
Develop statistical process monitoring systems
05
Lead a DMAIC project addressing complex operational problems
Six Sigma Black Belt Module (Days 8-10)
Module 04
01
Validate and improve the precision and accuracy of measurement systems to ensure high-quality data
02
Assess data distribution and select appropriate inferential statistical methods
03
Apply hypothesis testing and linear regression to identify and quantify non-quality factors
04
Design and conduct factorial Design of Experiments (DoE) to evaluate process parameter impact
05
Optimize process performance by analyzing experimental results and defining optimal operating conditions
Training Program
Lean Practitioner Module (Days 1-2)
Module 01
Lean Foundations
Principles and positioning of Lean Management
Continuous improvement and Kaizen approach
Process and Flow Analysis
Process and flow analysis (cycle time, takt time, bottlenecks)
Work-in-progress, lead time, and Little’s Law
Value Stream Mapping (VSM) and rhythm diagrams
Operational Improvement
Waste elimination and value-added analysis
Flow optimization and line balancing
Pull systems and production control (kanban, continuous flow)
Lean Practices and Performance
Visual management and Lean practices (5S, poka-yoke, SMED)
Operational performance and efficiency indicators (OPE, FPY, RTY)
Six Sigma Yellow Belt Module (Days 3-4)
Module 02
Lean Six Sigma Foundations
Principles and positioning of Lean Six Sigma
LSSx.0 problem typology and selection of the appropriate improvement trajectory
Problem Structuring
Project definition and SIPOC process mapping
Voice of the Customer and Critical-to-Satisfaction
Problem Analysis
Problem metrics and measurement planning
Root cause analysis using Pareto and Five Whys
Solution & Performance Management
Solution identification and evaluation
Performance monitoring and response plan
Six Sigma Green Belt Module (Days 5-7)
Module 03
Statistical Problem Solving
Application of the MAIC method to solve complex statistical problems
Project metrics definition and structured data collection
Measurement System & Process Analysis
Measurement system validation (Gauge R&R, linearity, bias)
Process capability analysis and Voice of the Process
Statistical Analysis
Process analysis using Y = f(X) logic and Ishikawa diagram
Graphical data analysis, correlation, and confidence intervals
Improvement Validation & Control
Statistical validation of improvements
Statistical Process Control (SPC) and control charts
Six Sigma Black Belt Module (Days 8-10)
Module 04
Measurement System Analysis
Measurement system analysis (MSA)
Concordance analysis (Kappa, Kendall)
Gauge R&R using the ANOVA method
Measurement system linearity and bias studies
Statistical Inference
Introduction to hypothesis testing
Normality testing
Equality of variances tests
Influence on central tendency (ANOVA, Mood’s median test, Kruskal–Wallis test)
Chi-square association test
Correlation and Regression
Pearson correlation analysis
Simple and multiple linear regression
Design of Experiments (DoE)
Design of Experiments fundamentals
Two-level factorial designs
Experiment resolution and number of repetitions
Experiment execution
Optimization
Analysis of main effects and interaction effects
Pareto of effects
Response surface methodology
Response optimizer
Learning Experience
Experiential & Inductive Pedagogy
Kaizen-based role-playing simulation of a cross-functional business process (order reception, production, invoicing, shipping)
DMAIC case study used as a structured guiding thread throughout the training
Statistical problem-solving applied to complex and “discernible” improvement cases
In-class Design of Experiments (DoE) simulations to optimize system parameters (paper flying machines case)
Process capability analysis applied to real production cases (screw manufacturing and printing processes)
Interactive Learning Environment
Small groups (maximum 12 participants) to foster interaction, idea-sharing, and peer learning
Active participation through practical exercises and collaborative problem solving
Assessment
Self-assessment and practice tests at the end of each module
Self-assessment and practice tests at the end of each module
Tools & Materials
Statistical software: JASP, Statoscopex, and Minitab
Excel-based statistical calculators and analytical models
Training materials provided in PDF format
Reference books :
LSSx.0 – 1. Flow Problems and Lean Management
LSSx.0 – 2. Discernible Problems and Methodological Foundation
LSSx.0 – 3. The Statoscope: Resolving Indiscernible and Related Statistical Problems
LSSx.0 – 1. Flow Problems and Lean Management
LSSx.0 – 2. Discernible Problems and Methodological Foundation
LSSx.0 – 3. The Statoscope: Resolving Indiscernible and Related Statistical Problems
Certification
The Lean Six Sigma Black Belt certification (LSSx.0™) is awarded upon successful completion of two separate examinations: Lean Practitioner Examination and Six Sigma Black Belt Examination.
Both exams validate knowledge aligned with the LSSx.0™ body of knowledge, ensuring participants can lead statistically complex improvement projects and drive high-performance operational outcomes.
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Upcoming availabilities
See all datesExamination Format
Online, closed-book exams with remote video monitoring
Lean Practitioner Examination : 25 multiple-choice questions – 50 minutes
Six Sigma Black Belt Examination : 45 multiple-choice questions – 90 minutes
Language: French or English
Exams must be completed within six months of training
Passing Criteria
Minimum score: 60% per exam
One retake per exam included in case of failure
Additional attempts available upon purchase of a new exam
