Role-Based Programme
RB1611

AI-Powered Continuous Improvement & Lean Six Sigma

Intelligent DMAIC, Process Analytics & Operational Excellence

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Duration
32 Hours
Level
Advanced
Delivery
Instructor-Led
Format
Capability Development

Programme Objectives

  • Develop advanced capability to apply AI across continuous improvement, Lean, Six Sigma, DMAIC, process optimisation, and operational excellence initiatives.
  • Use AI to analyse process data, cycle times, defects, waste, bottlenecks, customer feedback, quality metrics, and improvement records.
  • Apply AI-assisted techniques to problem definition, process mapping, root cause analysis, statistical interpretation, solution development, and control planning.
  • Build repeatable AI-enabled workflows for improvement-project management, action tracking, benefit monitoring, standardisation, and management reporting.
  • Design responsible AI-assisted improvement workflows with appropriate controls for data quality, statistical validity, assumptions, traceability, and human decision-making.

Tools covered

Generative AI AssistantsAI Search & ResearchSpreadsheet & Data AnalysisProcess Mapping AIStatistical Analysis ToolsRoot Cause Analysis ToolsLean Analysis ToolsQuality AnalyticsReporting & Dashboard ToolsWorkflow Automation

Who should attend

  • Continuous Improvement Managers
  • Lean Six Sigma Professionals
  • Lean Practitioners
  • Six Sigma Green Belts
  • Six Sigma Black Belts
  • Operational Excellence Professionals
  • Process Excellence Managers
  • Quality Managers
  • Quality Engineers
  • Process Improvement Analysts
  • Business Process Excellence Professionals
  • Operations Managers
  • Process Owners
  • Transformation Professionals
  • Continuous Improvement Team Leads

Prerequisites & Participant Readiness

  • Working knowledge of process improvement, Quality Management, Lean, Six Sigma, operations, or operational excellence
  • Familiarity with process maps, KPIs, defects, cycle times, root cause analysis, or improvement projects
  • Basic proficiency with spreadsheets, numerical data, documents, and workplace productivity applications
  • No previous AI course attendance required
  • No programming background required

TOC Modules

Concepts
  • Understanding Generative AI, analytical AI, process intelligence, and workflow automation
  • Mapping AI opportunities across Lean, Six Sigma, DMAIC, Kaizen, and process improvement
  • Understanding AI assistance versus statistical and process-owner judgement
  • Recognising risks related to weak data, incorrect assumptions, and misleading AI interpretations
Practical activities
  • Mapping an existing improvement lifecycle and identifying AI opportunities
  • Comparing manual and AI-assisted improvement activities
  • Creating a Continuous Improvement AI opportunity matrix

Scenarios

Business Problem to DMAIC Improvement Solution

Business Problem → Define → VOC / CTQ → Process Mapping → Measure → Data Analysis → Root Cause Validation → Improve → Control Plan → Benefit Tracking

Participants use AI-assisted Lean Six Sigma techniques to analyse a simulated operational problem, identify validated root causes, develop improvement options, and create a sustainable control plan.

Process Performance to Continuous Improvement System

Process KPIs + Defects + Delays + Customer Feedback + Improvement Actions → AI Analysis → Waste & Variation → Priority Opportunities → Automated Action Tracking → Control Dashboard → Management Review

Participants design an AI-enabled Continuous Improvement workflow that combines Lean, Six Sigma, process analytics, and automation to identify opportunities, manage improvement actions, and sustain performance gains.

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