ADT Academics

Adi Deere Technology

Lean Six Sigma Black Belt
Adi-Deere Technologies

Test Data
Test Data

Who is a Lean Six Sigma Black Belt?

The Certified Lean Six Sigma Black Belt is a professional who can explain Six Sigma philosophies and principles, including supporting systems and tools. A Black Belt should demonstrate team leadership, understand team dynamics, and assign team member roles and responsibilities. Black Belts have a thorough understanding of all aspects of the DMAIC model in accordance with Six Sigma principles. They have basic knowledge of lean enterprise concepts, are able to identify non value-added elements and activities, and are able to use advanced analytical tools.


Course Overview

Training Duration

Participants will attend 54 hours of facilitator led classroom training for Black Belt in addition to 36 hours of Green Belt classroom training

Training Package
  • Hard copy of Black Belt Book of Knowledge
  • Preparatory module
  • Analysis data files and templates
  • 30 completed case studies
  • 10 e-books on Lean Six Sigma related content
  • 2 Simulation projects
  • 2 Sample question papers
  • Lean Six Sigma Black Belt Exam Fee
  • Refreshment and lunch on training days
  • 54 PDUs for PMI
For comprehensive workshop and certification information, Please email us at

Trainer Details Coming Soon...!

Certification Exam

Each certification candidate is required to pass a written examination that consists of multiple choice questions measuring comprehension of the Body of Knowledge. The Six Sigma Black Belt certification examination is a 4-hour, 150 multiple-choice question examination. It is only offered in English.


Trainer Testimonials Coming Soon...!

Course Content

  • Voice of the Customer, Business & Cost of Poor Quality
  • Kano Analysis
  • Quality Function Deployment
  • Goal-Means Diagram & CTQ Drill down tree
  • Prioritization matrix & DMAIC screening
  • Business Case & Project Charter
  • Project Management (PM) Tools
  • Process Characteristics
  • Data Collection
  • Measurement System Analysis which includes Gage R&R, Attribute Agreement Analysis
  • Basic Statistics and Probability
  • Graphical plots like histogram, Dot plot, Individual value plot, Multi-vari chart, Time series plot
  • Rational Sub-grouping
  • Sigma level for overall & sub-grouped data
  • Process Capability Indices
  • Goal Setting and Feasibility
  • Failure Mode and Effects Analysis(FMEA)
  • Value stream mapping
  • Qualitative Screening
  • Exploratory Analysis
  • Measuring & Modeling Relationships between Variables
  • Sample Size determination for Hypothesis test
  • Sample size determine for Lot testing
  • Hypothesis testing for normally distributed data which includes t test, ANOVA, Bartlett, Levene, F-test, ANOM
  • Hypothesis testing for non-normal data which includes 1-sample sign, Mann-Whitney, Moods-Median, Kruskal Wallis
  • Hypothesis testing for discrete data which include 2-proportion, chi-square test
  • Correlation & Regression including discussion on R-squared, R-squared predicted
  • Design of Experiments (DOE) includes Full Factorial & Fractional Factorial experiments
  • Y=f(x) model development
  • Graphical plots includes Main effects Plot, Interaction Effects Plot,Cube Plot, Surface Plot, Contour Plot
  • Response Optimization using constraints
  • Theory of Constraints for Solutioning
  • Lean Methods like SMED, JIT, Kanban, Total Productive Maintenance, Poka Yoke
  • Full Scale Implementation Project Plan & Validation
  • Control Plan which includes Risk mitigation dashboard,Poka Yoke dashboard, Audit & Inspection Plans
  • Statistical Process Control (SPC) – Control charts including p, np, c,u, Xbar-R, Xbar-S, I-MR chart
  • Solution Documentation & Financial Benefits Projection
  • Executive Summary & Hand over to Process Owner

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