AI-Powered Root Cause Analysis Lean Six Sigma & CAPA

What you'll learn

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Apply Root Cause Analysis tools such as 5 Whys, Fishbone, SIPOC, Pareto, FMEA, and Fault Tree Analysis.
Use Generative AI prompts to define problems, explore causes, validate assumptions, and improve RCA quality.
Build stronger CAPA plans by linking root causes to corrective actions, preventive actions, owners, and measures.
Identify weak RCA logic, avoid blame-based conclusions, and separate evidence from assumptions.
Use AI responsibly for RCA while protecting sensitive, confidential, and regulated business data.
Complete a practical AI-powered RCA report using downloadable templates and a capstone case study.
Requirements

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No AI or programming experience is required. The course explains how to use prompts step by step.
Basic familiarity with business, manufacturing, quality, operations, or process improvement will be helpful.
Access to an AI tool such as ChatGPT, Claude, Gemini, or Microsoft Copilot is recommended for practice.
A willingness to apply structured problem-solving methods to real workplace problems.
Description

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This course contains the use of artificial intelligence.
Most root cause investigations stop at the first plausible answer.
I have watched it happen for sixteen years across pharma, electronics and contract manufacturing. A deviation gets a 5 Whys in twenty minutes, the "root cause" turns out to be a person, the corrective action is retraining, and the same problem is back within a quarter. Not because the tools are wrong. Because doing them properly takes time and discipline that nobody has on a bad day.
Generative AI changes the time part. It does not change the discipline part. This course teaches both together.
What You Will Learn

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- The six classic Lean Six Sigma RCA tools: 5 Whys, Fishbone, Pareto, Process Mapping, Fault Tree and the Cause & Effect Matrix. Each one comes with a copy-and-paste AI prompt.
- A six-stage framework (Define, Discover, Analyze, Validate, Act, Learn) that takes any problem from confusion to a fix that lasts.
- Where AI is genuinely useful inside an investigation, and where it will confidently mislead you if you let it.
- How to build an always-on RCA copilot for your whole team.
- How to write a CAPA with a real preventive action instead of a symptom patch.
- How to use AI without exposing confidential or regulated data.
How it is taught
Ten short modules, about 65 minutes of video. Four fully worked cases: a factory yield loss, a regulated pharma deviation, a supply-chain delay and a flood of customer complaints. Same method, four very different worlds.
You finish with a final project on a real problem from your own work, or a sample case if you would rather not use company data. You hand in four deliverables: a 5W1H problem statement, an analysis using at least two tools, a validated root cause backed by evidence, and a CAPA. That is a portfolio piece you can show a manager or an auditor.
Who this is for
Quality, operations, engineering and continuous-improvement professionals who are tired of investigations that do not stick. No AI experience is needed. Access to any AI assistant is enough.
Bring one recurring problem with you. You will have solved it by the end.
Who this course is for

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Quality professionals, engineers, and CAPA owners who want to improve root cause investigations.
Lean Six Sigma, Continuous Improvement, and Operational Excellence practitioners using RCA tools
Manufacturing, pharma, medical device, logistics, and operations professionals solving repeat problems.
Managers and team leaders who want to use AI responsibly for structured business problem solving.
Anyone who wants practical AI prompts for 5 Whys, Fishbone, CAPA, and RCA report writing.
Homepage

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