AI6SIGMA ADVANCED AUTOMATION
3-Day AI-Enabled Lean Six Sigma Automation with JMP & JSL
Advanced Engineering & Operations Workflow Automation
Turn validated recurring analysis into secure, repeatable JMP/JSL workflows. ChatGPT and Microsoft Copilot can assist workflow design, scripting, interpretation, and documentation; JMP validates analytical logic and statistical results, and professionals retain important decisions.
Who This Course Is For
Designed for engineering, manufacturing, quality, reliability, process-improvement, and operations professionals in organizations that use JMP and want to automate repeatable analytical and improvement workflows.
Participants should have access to JMP. Prior JSL programming experience is not required.
What Participants Learn
Build Repeatable JMP/JSL Analytical Workflows
Integrate AI Assistance Into Validated Analysis
Create Statistical Validation Gates
Build Human-in-the-Loop Review and Escalation
Operationalize Monitoring and Reporting
THE AI6SIGMA AUTOMATION DIFFERENCE
Different from Generic AI Automation
This training uses an 11-step automation framework for validated engineering, quality, process-improvement, and analytical workflows—not uncontrolled autonomous decision-making. JSL converts validated recurring analysis into repeatable execution that can remain inside the company's secured environment.
11-STEP AUTOMATION FRAMEWORK
Validate, Build, and Operationalize
DAY 1 — VALIDATE BEFORE AUTOMATING
Process/problem framing • current-state workflow • JMP statistical baseline • decision logic • automation suitability • failure modes • validation criteria • JSL automation foundations
DAY 2 — BUILD THE AI-ASSISTED WORKFLOW
Data handling • JMP/JSL workflow orchestration • AI-assisted analysis and interpretation • exception detection • statistical validation gates • recurring analysis • reporting • human approval checkpoints
DAY 3 — OPERATIONALIZE, CONTROL & GOVERN
Repeatable automation • monitoring • control logic • audit trails • exception escalation • deployment considerations • responsible AI governance • end-to-end automation exercise
Practical Automation Use Cases
process-capability monitoringSPC and quality exception reviewdefect and yield trend analysisAI-assisted root-cause triagestandardized recurring JMP analysessupplier-quality and validation workflowsmanagement-ready recurring reportingevidence-validation and approval workflows
The course focuses on analytical and process-improvement workflow automation rather than autonomous equipment or PLC/machine-control programming.
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.
JMP Access
This course is designed primarily for organizations already using JMP. Participants require JMP access for hands-on exercises and for ongoing deployment of JMP/JSL automation workflows.
Implementation Support
Company teams may request follow-on support to adapt validated course workflows to their own quality, engineering, manufacturing, or operational processes.
Bring Validated AI-Assisted Automation to Your Team
Ask about upcoming training dates, JMP-enabled team delivery, or private company automation training.
Request Training InformationHOW 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.