DEFINE
Project charter • problem statement • business objectives • VOC / CTQ • SIPOC • process mapping • scope • stakeholder alignment
AI LEAN SIX SIGMA GREEN BELT
5-Day AI-Powered Lean Six Sigma Green Belt
Build complete DMAIC capability while ChatGPT and Microsoft Copilot assist problem framing, investigation, analysis planning, interpretation, documentation, and management-ready reporting, with independent JMP statistical evidence.
Who This Program Is For
For engineers, program managers, engineering program managers (EPMs), technical program managers (TPMs), and improvement professionals building a practical DMAIC and statistical foundation for technical improvement work.
THE AI6SIGMA DIFFERENCE
What AI-Powered Green Belt Means
Structured AI-assisted workflows strengthen the full DMAIC roadmap. AI accelerates problem framing, investigation, analysis planning, interpretation, root-cause thinking, documentation, and reporting while DMAIC and JMP provide discipline and validation.
THE COMPLETE DMAIC ROADMAP
Structured Improvement From Definition Through Control
MEASURE
Process measures • data planning • measurement system analysis • process capability • baseline performance • variation / defects • JMP exploration
ANALYZE
Exploratory analysis • confidence intervals • hypothesis testing • ANOVA • regression • defect and non-normal analysis • root-cause investigation • hallucination detection • statistical validation
IMPROVE
Generate alternatives • evaluate solutions • Design of Experiments • process optimization • implementation recommendations
CONTROL
SPC • control charts • control plans • monitoring • standardization • sustainment • documentation • management-ready reporting • closeout
Where AI Assistance Adds Value
Analysis PlanningJMP InterpretationRoot Cause InvestigationDecision ValidationProject DocumentationManagement Reporting
THE AI6SIGMA STRUCTURED METHODOLOGY
The AI6Sigma Problem Solving Approach
AI6Sigma teaches a structured 4-stage methodology for AI-powered process improvement. Defined step-by-step workflows across every stage move participants from a clearly framed problem to statistical evidence, AI-assisted validation, and repeatable execution rather than ad hoc prompting or unsupported AI outputs.
Frame the Problem
Problem Framing — 5 Steps Where ApplicableDefine the process problem, CTQs, scope, performance gap, and decision criteria using a structured problem-framing workflow.
Establish Statistical Evidence
2-Step Statistical Evidence WorkflowUse Lean Six Sigma methods, calculations, JMP analysis, and practical case studies to establish what the data actually supports and develop defensible conclusions.
Accelerate & Validate with AI
6-Step AI-Assisted Validation WorkflowAccelerate investigation, analysis planning, interpretation, and reporting while validating critical conclusions against JMP statistical evidence.
Implement, Control & Automate
11-Step Automation Framework in the Automation ProgramTurn validated recurring analysis into controlled, repeatable JMP/JSL workflows that can remain inside the company's secured environment while professionals retain decision ownership.
Structured steps within each stage make the workflow repeatable, teachable, and review-ready.
AI accelerates. JMP validates. Professionals own the decision. Secure automation scales validated improvement.
RESPONSIBLE AI IN LEAN SIX SIGMA PROJECTS
Use GenAI Without Lowering the Evidence Standard
✓ Separate AI suggestions from evidence
✓ Detect hallucinated reasoning
✓ Verify interpretation against JMP
✓ Challenge overconfident conclusions
✓ Document evidence
✓ Preserve human review
✓ Communicate uncertainty
5-DAY GREEN BELT TRAINING
Explore Related Training
Plan Your Training
AI6Sigma builds on Global Lean Sigma’s 20+ years of practical engineering problem-solving training.
Live Instructor-Led Learning
Attend scheduled virtual sessions or arrange onsite training for your team. Ask questions, discuss case results with peers and receive instructor feedback.
Apply the Learning at Work
Reuse project and problem-framing templates, AI prompts, validation checks and decision summaries with teammates on suitable improvement opportunities.
Experience & Software
No prior AI or JMP experience required. Familiarity with basic statistics and data analysis is recommended. Use a company-approved AI tool such as ChatGPT or Microsoft Copilot. Training demonstrations and exercises use JMP with supplied practice datasets.
Participant Feedback from Prior Global Lean Sigma Training
Rachel Johnston, Technical Program Manager, Intel
“The material and examples were very useful and now feel confident to do activities/use tools to solve business problems. Highly recommend this course. Instructor was top-notch.”
Feng Zhang, PhD, Director of Advanced Data Analytics, Western Digital
“Richard is one of the best instructors I have had. He demonstrates both width & depth of knowledges. Strong recommendation of this Black Belt training.”