Lean Six Sigma Green Belt

Programme Summary

This intensive programme develops practical capability to structure and analyse a defined improvement project using Lean Six Sigma. Participants apply DMAIC to a supplied business case, combining customer requirements, process analysis, measurement evaluation and selected statistical methods. Guided exercises build a justified improvement and control proposal, while clearly separating classroom achievement from workplace project delivery and separate professional certification requirements.

Training Objectives

1 Develop structured leadership of bounded improvement projects; 2 Strengthen measurement and statistical decision-making skills; 3 Connect root causes with effective improvement choices; 4 Integrate Lean methods with variation reduction; 5 Build practical control and benefit verification arrangements.

Learning Outcomes

1 Construct a clear charter and customer requirements; 2 Evaluate measurement suitability and baseline process performance; 3 Select and interpret appropriate statistical analyses; 4 Develop justified improvement options and pilot arrangements; 5 Prepare a control plan and benefit verification approach.

Target Audience

Continuous Improvement Specialists; Quality Engineers; Process Engineers; Operations Analysts; Manufacturing Supervisors; Project Improvement Leaders.

Target Industries

Manufacturing; Food Processing; Healthcare Administration; Financial Operations; Logistics; Technology Support Services.

Course Contents

• Module 1 Green Belt Role and Project Selection: DMAIC governance and project suitability; Sponsor engagement and resource commitments; Professional boundaries and evidence integrity.
• Module 2 Customer Needs and Critical Requirements: Voice of customer data collection; Translating needs into measurable characteristics; Requirement priorities and performance expectations.
• Module 3 Project Charter and Stakeholder Planning: Problem baseline scope and goal statements; Benefits assumptions and milestone planning; Stakeholder communication and change readiness.
• Module 4 Process Definition and Mapping: SIPOC boundaries and process ownership; Detailed flow maps and handoffs; Process inputs outputs and failure points.
• Module 5 Lean Process Analysis: Waste identification and flow interruptions; Value stream measures and bottlenecks; Standard work and workplace organisation.
• Module 6 Measurement and Data Collection Planning: Operational definitions and data types; Sampling strategy and representative collection; Data quality checks and traceability.
• Module 7 Measurement System Evaluation: Repeatability reproducibility and measurement bias; Attribute agreement and reference decisions; Interpreting studies and prioritising improvements.
• Module 8 Descriptive Statistics and Visual Analysis: Central tendency dispersion and distribution shape; Graphical comparisons and stratified patterns; Outliers missing values and data context.
• Module 9 Probability Sampling and Estimation: Common distributions and practical assumptions; Sampling uncertainty and confidence intervals; Sample-size considerations and interpretation limits.
• Module 10 Statistical Process Control: Chart selection and rational subgroups; Control limits and special-cause signals; Appropriate responses and stable baselines.
• Module 11 Process Capability and Baseline Performance: Capability indices and specification relationships; Stability and distribution assumption checks; Defect measures and performance limitations.
• Module 12 Root Cause and Relationship Analysis: Cause-and-effect and causal hypothesis development; Evidence checks and process-based reasoning; Prioritising causes for further investigation.
• Module 13 Hypothesis Tests for Continuous Data: Questions assumptions and test selection; Mean comparisons and confidence interpretation; Practical significance versus statistical significance.
• Module 14 Analysing Attribute and Grouped Data: Proportion comparisons and count-based questions; Association tests and contingency tables; Interpreting uncertainty and test limitations.
• Module 15 Correlation and Regression Applications: Relationship patterns and regression models; Residual checks and explanatory limitations; Prediction boundaries and confounding considerations.
• Module 16 Introduction to Designed Experiments: Factors responses and controlled comparisons; Basic factorial designs and interactions; Randomisation replication and experiment safety.
• Module 17 Risk Evaluation and Improvement Selection: FMEA reasoning and solution risk review; Selection criteria and mistake-proofing options; Expected effects and unintended consequences.
• Module 18 Pilot Planning and Change Implementation: Pilot scope measures and decision criteria; Implementation ownership and stakeholder engagement; Evaluating pilot results against baseline.
• Module 19 Control Planning and Process Handover: Control characteristics frequency and responsibilities; Reaction plans and standard work updates; Training handover and sustained monitoring.
• Module 20 Benefits Review and Project Presentation: Benefit assumptions and verification evidence; DMAIC storyline and defensible recommendations; Lessons learned and further development needs.

Assessment

• 100 single best answer questions, including applied scenarios; one mark per question.
• 150 minute invigilated digital examination with identity verification. Approved accessibility adjustments preserve the assessed competence.
• Supplied formulas, statistical tables and calculator permitted; internet and AI prohibited. Approved statistical software permitted for practical assessment.
• Individual applied assessment (90 minutes): Using the supplied project dataset and analysis templates, submit a concise DMAIC case containing a charter, baseline interpretation, justified causal analysis, improvement recommendation and control plan, then explain key assumptions and benefit-verification measures.
• Assessment criteria: Coherent DMAIC reasoning and appropriate analytical choices; Correct interpretation of data assumptions and uncertainty; Feasible improvement control and benefit verification plan.
• Pass each component separately: 75/100 written marks (75%) and at least 70% on the applied task.
• All mandatory criteria must pass: Do not fabricate data or misrepresent statistical evidence.
• Individual results and feedback are provided. One reassessment may follow coaching under the published enrolment terms.

Certification

• Successful learners receive a TQCSI Arabia digital Certificate of Successful Completion.
• The certificate records the learner name, exact programme title, teaching hours, completion date and unique verification reference.
• Verified identity, full attendance and separate written and applied passes are required; all mandatory critical criteria must be met.
• Proposed issue target: within 30 calendar days of approved results and settlement of applicable fees.
• Records assessed Green Belt course completion; independent personnel certification and verified workplace project performance require separate evidence.
• Attendance confirmation may record completed hours for unsuccessful learners; it does not certify successful completion.

Programme Profile

Number of daysNumber of daysNumber of days

555

Total teaching hoursTotal teaching hoursTotal teaching hours

35 hours; breaks, pre course work and formal final assessments excluded.35 hours; breaks, pre course work and formal final assessments excluded.35 hours; breaks, pre course work and formal final assessments excluded.

Delegates allowedDelegates allowedDelegates allowed

Maximum 16 delegates.Maximum 16 delegates.Maximum 16 delegates.

Training prerequisitesTraining prerequisitesTraining prerequisites

Yellow Belt knowledge or equivalent DMAIC familiarity is required. Spreadsheet confidence, basic descriptive statistics and experience of organisational processes are strongly recommended.Yellow Belt knowledge or equivalent DMAIC familiarity is required. Spreadsheet confidence, basic descriptive statistics and experience of organisational processes are strongly recommended.Yellow Belt knowledge or equivalent DMAIC familiarity is required. Spreadsheet confidence, basic descriptive statistics and experience of organisational processes are strongly recommended.

Pre course assignment and assessmentPre course assignment and assessmentPre course assignment and assessment

Complete a 45-minute statistics and DMAIC diagnostic and review the supplied project case, dataset structure and customer requirements.Complete a 45-minute statistics and DMAIC diagnostic and review the supplied project case, dataset structure and customer requirements.Complete a 45-minute statistics and DMAIC diagnostic and review the supplied project case, dataset structure and customer requirements.

End of course assessmentEnd of course assessmentEnd of course assessment

100 question written exam (150 minutes) and individual applied task (90 minutes).100 question written exam (150 minutes) and individual applied task (90 minutes).100 question written exam (150 minutes) and individual applied task (90 minutes).

Passing criteriaPassing criteriaPassing criteria

75% written and 70% applied, passed separately; full attendance. All mandatory criteria must pass.75% written and 70% applied, passed separately; full attendance. All mandatory criteria must pass.75% written and 70% applied, passed separately; full attendance. All mandatory criteria must pass.