PRACTICAL ROOT CAUSE ANALYSIS DATA-DRIVEN APPROACH WITH AI ASSISTANCE
17 - 18 AUGUST 2026
COURSE INTRODUCTION
This programme develops a disciplined approach to solving recurring operational and quality problems using structured root cause analysis, reliable evidence and AI-assisted analysis. Participants strengthen problem definition, data interpretation, 5 Why and cause-validation skills, then design corrective actions using control hierarchy and Poka-Yoke principles. Practical cases show how AI can improve analysis without replacing engineering judgement.
COURSE OBJECTIVES
By the end of this programme, participants should be able to:
- Define operational problems using clear facts, scope and measurable evidence.
- Apply structured RCA methods, including 5 Why and cause-and-effect analysis.
- Use Pareto, trend and stratification data to validate possible causes.
- Use AI tools to improve problem statements, explore patterns and test reasoning.
- Evaluate corrective actions using control hierarchy and Poka-Yoke principles.
- Develop permanent actions with clear ownership, verification and recurrence controls.
WHO SHOULD ATTEND
This programme is suitable for engineers, supervisors, quality and manufacturing personnel, technical managers, maintenance teams and problem-solving leaders responsible for eliminating recurring issues.
COURSE CONTENT
- RCA foundations, structured problem solving and common mindset traps
- Strong problem statements and cause-and-effect logic
- 5 Why, fishbone analysis and root-cause validation
- Pareto, trend and stratification data for evidence-based analysis
- AI-assisted problem definition, pattern exploration and reasoning support
- Poka-Yoke, Zero Defect thinking and control hierarchy
- Corrective-action design, ownership and effectiveness verification
- Practical RCA case analysis and solution development
