Role-Based Programme
RB1610

AI-Powered Continuous Improvement & Lean Six Sigma

Smarter Process Analysis, Waste Reduction & Performance Excellence

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Duration
16 Hours
Level
Intermediate
Delivery
Instructor-Led
Format
Capability Training

Programme Objectives

  • Apply AI across Continuous Improvement and Lean Six Sigma activities including process analysis, waste identification, root-cause analysis, measurement, and improvement planning.
  • Use AI-assisted techniques to accelerate DMAIC activities, process mapping, Voice of Customer analysis, defect analysis, and problem solving.
  • Analyse operational and quality data to identify variation, bottlenecks, waste, recurring problems, and improvement opportunities.
  • Develop structured improvement workflows covering problem definition, measurement, analysis, solution development, implementation, and control.
  • Apply responsible AI practices covering data accuracy, statistical interpretation, evidence validation, process ownership, and human judgement.

Tools covered

Generative AI AssistantsProcess Mapping SupportLean AnalysisSix Sigma AnalyticsSpreadsheet AnalysisRoot Cause AnalysisVoice of Customer AnalysisKPI AnalysisImprovement ReportingWorkflow Automation

Who should attend

  • Continuous Improvement Professionals
  • Lean Practitioners
  • Lean Six Sigma Professionals
  • Process Excellence Professionals
  • Operational Excellence Professionals
  • Quality Managers
  • Quality Engineers
  • Process Improvement Managers
  • Business Excellence Professionals
  • Six Sigma Green Belt Professionals
  • Process Analysts
  • Operations Managers
  • Quality Assurance Professionals
  • Quality Management Team Leads

Prerequisites & Participant Readiness

  • Working knowledge of quality, process improvement, operations, or business processes
  • Familiarity with basic Lean, Six Sigma, or problem-solving concepts is helpful
  • Basic spreadsheet and data-analysis skills
  • Basic awareness of Generative AI is helpful
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, analytics, automation, and their role in process improvement
  • Identifying AI opportunities across Lean, Six Sigma, problem solving, and operational excellence
  • Understanding AI assistance versus process-owner and improvement-professional judgement
  • Recognising risks related to poor-quality data, unsupported conclusions, and over-automation
Practical activities
  • Mapping a typical improvement lifecycle to AI-assisted activities
  • Identifying repetitive analytical and documentation tasks suitable for AI support
  • Comparing traditional and AI-assisted improvement workflows

Scenarios

Process Delay to Lean Six Sigma Improvement Plan

Business Problem → AI-Assisted Problem Definition → SIPOC → Process Map → Waste Identification → Data Analysis → Root Cause → Improvement Actions → Control Plan

Participants analyse a simulated process experiencing delays, identify waste and root causes, develop prioritised improvements, and create a structured control plan using the DMAIC approach.

Quality Performance Data to Continuous Improvement Project

Defect Data + Cycle-Time Data + Customer Feedback → AI Analysis → Pareto Priorities → Root Causes → Solution Options → Pilot Plan → KPI Monitoring → Management Report

Participants combine operational, quality, and customer information to identify the highest-impact improvement opportunities and prepare a management-ready Lean Six Sigma improvement proposal.

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