ENGINEERING TRAINING
3-Day Product & Hardware Engineering Problem-Solving with AI + JMP
Integrate AI, JMP and practical methods to compare design and test performance, identify influential factors, and plan experiments for better product design and quality performance.
Who This Course Is For
Product, Hardware, Systems, and Validation & Test engineers comparing design alternatives, identifying performance drivers, and planning experiments to improve product design and quality performance.
Choose Your Training Approach
Learn an integrated engineering problem-solving workflow using ChatGPT or Microsoft Copilot, independent JMP statistical validation, and reusable workplace prompts and checklists.
Prefer training without generative AI? Explore Global Lean Sigma →
THE AI6SIGMA DIFFERENCE
What AI-Powered Means in This Program
Use ChatGPT or Microsoft Copilot to frame product and hardware questions, plan design and test comparisons, investigate influential factors, and explain regression and DOE results. Independently check AI interpretations against JMP evidence, design requirements and test conditions to develop defensible recommendations for product design and quality performance.
What Participants Learn
Identify Performance Drivers
Model Relationships With Regression
Plan and Interpret Factorial Experiments
Validate AI Conclusions With JMP Evidence
COURSE TOPICS
Focused AI-Assisted Analysis and Improvement
AI6Sigma Workflow & JMP Orientation
Course overview • optional JMP orientation • problem statements • data quality and assumption checks
Use ChatGPT or Microsoft Copilot with independent JMP analysis.
Engineering Comparisons & Uncertainty
Confidence intervals • hypothesis testing for means and variances • ANOVA • JMP and GenAI exercises
Relationships & Performance Drivers
Correlation and relationship analysis • simple linear regression • multiple regression • JMP and GenAI exercises
Experimental Planning & DOE
Factors and responses • full factorial DOE • fractional factorial DOE • main effects • interactions • technical interpretation
Independent Practice & Workplace Application
AI/JMP evidence comparison • decision explanation • independent product and hardware problem-solving case • workplace application and review
Where AI Assistance Adds Value
Analysis PlanningJMP InterpretationRoot Cause InvestigationDecision ValidationManagement-Ready Reporting
RESPONSIBLE AI & DECISION VALIDATION
Move Faster Without Lowering the Evidence Standard
✓ Distinguish AI suggestions from statistical evidence
✓ Identify unsupported assumptions
✓ Verify interpretation against JMP output
✓ Avoid overstating statistical results
✓ Document the basis for recommendations
✓ Retain human ownership of final decisions
Plan Your Training
AI6Sigma builds on Global Lean Sigma’s 20+ years of practical engineering problem-solving training.
Live Instructor-Led Learning
Attend scheduled 3-day virtual sessions or arrange onsite training for your team. Ask questions, discuss findings with peers and receive instructor feedback.
Apply the Learning at Work
Take away reusable prompts, validation checklists and practical templates to practice with teammates and support engineering improvements.
Experience & Software
No prior AI or JMP experience required. Familiarity with basic statistics and engineering data is recommended. Instruction uses JMP with ChatGPT or Microsoft Copilot, subject to company access policies.
HOW YOU WILL WORK MORE PRODUCTIVELY AFTER AI6SIGMA TRAINING
Use AI to Accelerate Analysis. Check the Evidence. Explain the Decision.
Students get an AI answer, run the appropriate analysis independently in JMP, compare the evidence and assumptions, correct errors, and explain the decision.
Accelerate analysis
Use GenAI to support investigation, interpretation and communication.
Check before acting
Evaluate statistical claims with independent JMP analysis and engineering judgment. Agreement alone does not establish validity.
Apply a consistent method
Reduce unsupported reasoning and analytical rework with a repeatable workplace practice.
FROM CLASSROOM TO WORKPLACE
Take a Repeatable Practice Back to Work
Use a condensed course PDF and a workplace application packet: a problem statement template, reusable prompts, a validation checklist, a decision summary template and course-specific practice materials.
Practice independently with course datasets and guidance. Additional project coaching and implementation support can be discussed separately.