Lean Six Sigma Black Belt Curriculum

The programme

Programme overview

Candidates must have successfully completed the Lean Six Sigma Green Belt certification before enrolling in the Black Belt course. The Green Belt certification ensures that candidates have a foundational understanding of Six Sigma principles, basic statistical tools, and process improvement methodologies, which will be built upon in this advanced course.

Who should attend

Who is this programme for?

Contact Ratomac to confirm suitability for your role and prior experience.

Learning outcomes

What you will learn

Review the detailed outline below and ask Ratomac to confirm the learning outcomes for your selected programme.

Explore the programme

Detailed programme outline

Week 1: Fundamentals of Six Sigma and DMAIC Methodology

Day 1: Introduction to Six Sigma and Statistical Foundations

• What is Six Sigma?Overview of Six Sigma methodologyThe goal of Six Sigma: Process improvement and defect reductionThe philosophy of Six Sigma: DMAIC (Define, Measure, Analyse, Improve, Control)
• The Normal DistributionKey properties of the Normal distributionUnderstanding the significance of standard deviation and meanZ-scores and probabilitiesThe role of the Normal distribution in process improvement
• Central Limit Theorem (CLT)Explanation of the CLT and its significance in process analysisSampling distribution and its implications for statistical testing
• The t DistributionWhen and why to use the t-distributionDifferences between the t and normal distributions

Day 2: Define Phase – Project Initiation and SIPOC Mapping

• Define Stage in DMAICProject scope and goals: Defining what constitutes success in the projectProject Charter: How to develop a clear project charter that outlines objectives, team roles, and goals
• Creating a SIPOC DiagramUnderstanding SIPOC (Suppliers, Inputs, Process, Outputs, Customers)How to map a process at a high level to identify critical inputs and outputs
• Critical to Quality Measure (CTQ)Understanding CTQ and how it aligns with customer requirementsTechniques to translate customer needs into measurable outputs
• Dimensions of Service and Product QualityThe 5 dimensions of service quality: Tangibles, Reliability, Responsiveness, Assurance, EmpathyThe 4 dimensions of product quality: Performance, Features, Reliability, Durability
• Quality Function Deployment (QFD)Introduction to QFD and the House of QualityTranslating customer needs into product specifications

Day 3: Measure Phase – Data Collection, Variation, and Process Capability

• Key Measures for Process PerformanceKey performance indicators (KPIs) and how to define them for specific projectsUnderstanding process metrics: Cycle time, throughput, defect rates, etc.
• Data Collection Planning and ExecutionHow to plan data collection to ensure it’s systematic and unbiasedTechniques to ensure data accuracy and consistency
• Displaying Process VariationTools for visualizing variation: Histograms, box plots, scatter plots
• Measurement System Analysis (Gage R&R)How to assess the accuracy and reliability of measurement systemsGage R&R study: Precision vs. accuracy
• Process Capability Analysis (Advanced)Calculating process capability indices (Cp, Cpk)Understanding process performance using sigma levels
• Sigma Performance and Calculating Sigma LevelsCalculating sigma level of a processThe importance of achieving higher sigma levels for improved quality

Day 4: Analyse Phase – Identifying Root Causes and Analysing Data

• Stratification TechniquesBreaking down data by categories to identify patterns and trends
• Tree DiagramsUsing tree diagrams for breaking down complex problems into manageable components
• Correlation and Simple Linear RegressionUnderstanding correlation vs causationUsing linear regression to model relationships between variables
• Statistical Process Control (SPC)The role of SPC in monitoring process behaviourTypes of control charts: X-bar, R-chart, p-chart, etc.
• T-testPerforming t-tests to compare sample meansUnderstanding p-values and interpreting statistical significance
• One-way and Two-way ANOVAPerforming ANOVA to analyse variance across multiple groups or factors
• 5 Whys and Fishbone Diagram (Ishikawa)Root cause analysis using the 5 Whys techniqueFishbone diagrams for visualizing potential causes of problems
• Cause and Effect AnalysisTechniques to identify root causes of process issues
• Failure Mode and Effects Analysis (FMEA)Identifying and prioritizing potential failure modes in processesUsing FMEA to assess risks and prioritize actions

Day 5: Operational Analysis and Lean Tools

• Standard Operating Procedures (SOPs)Importance of SOPs in maintaining process consistency and quality
• Capacity UtilizationAnalysing and improving process capacityHow to calculate and optimize capacity utilization
• Lean AccountingIntroduction to lean accounting principlesCost structures, value stream costing, and financial benefits of Lean
• Stakeholder AnalysisIdentifying and managing key stakeholders in Six Sigma projectsTechniques to ensure stakeholder engagement and buy-in

End of Week 1 Exam (3 hours)

• Written test covering all topics from Week 1
• Multiple-choice, short answer, and scenario-based questions

Week 2: Advanced Analysis, Improvement Techniques, and Control Tools

Day 8: Advanced Data and Process Analysis

• Data and Process Analysis TechniquesAdvanced techniques for deeper process analysis
• Root Cause AnalysisMethods for analysing and identifying root causes in complex problems
• Quantifying the Gap/OpportunityHow to quantify performance gaps and assess opportunities for improvement
• Hypothesis Testing and Power of TestsConducting hypothesis tests to validate assumptionsUnderstanding statistical power and sample size determination
• Descriptive Tests and Multiple RegressionUsing descriptive statistics to summarize dataMultiple regression analysis for complex models
• Design of Experiments (DOE)Planning and conducting experiments to optimize process variablesIntroduction to factorial designs and response surface methodology
• Taguchi MethodsRobust design techniques to minimize variation in product and process performance

Day 9: Improve Phase – Solution Generation and Testing

• Generating and Testing SolutionsBrainstorming solutions to process issuesUsing creativity and structured methods (e.g., TRIZ) to generate innovative solutions
• Selecting the Best SolutionsCriteria for evaluating and selecting optimal solutions based on cost, feasibility, and impact
• Designing Implementation PlansDeveloping detailed plans for implementing improvement solutions
• Time Series AnalysisAnalysing trends and patterns over time to make data-driven decisions
• Cross-CorrelationAnalysing relationships between time-series data
• Binary Logistic RegressionPredicting categorical outcomes (yes/no) using logistic regression
• Chi-Square TestTesting relationships between categorical variables using chi-square tests

Day 10: Control Phase – Ensuring Sustainability

• Monitoring PlansDeveloping ongoing monitoring and control plans to track improvements
• Process StandardizationStandardizing processes to ensure consistent results
• Response PlansCreating response plans to address any issues or deviations from expected outcomes
• Transfer of OwnershipEnsuring successful transition of process improvements to operational teams
• Reliability EngineeringTechniques for ensuring process reliability and minimizing failure rates
• Total Productive Maintenance (TPM)TPM principles for improving machine reliability and uptime
• Poka YokeDesigning error-proofing mechanisms to prevent defects
• Cellular ManufacturingImplementing cellular manufacturing layouts to optimize flow and reduce waste
• Characteristics of LeanThe key principles of Lean: Value, value stream mapping, pull systems, flow, and continuous improvement

End of Week 2 Exam (3 hours)

• Written test covering all topics from Week 2
• Multiple-choice, short answer, and case-based questions

Post-Course Project (To be completed after course completion)

• Project Scope: Apply Lean Six Sigma tools and techniques to a real-world process with measurable financial savings
• Project Deliverables: Charter, data collection, analysis, solution generation, and final report with financial savings demonstrated
• Presentation: A final presentation summarizing the project and the financial impact

Learning approach

How you will learn

Our diverse instructional approaches ensure effective learning:

– Lectures & Presentations: Engage with expert-driven, stimulating content.– Course Material: Access well-crafted supporting resources.– Group Work: Collaborate on discussions and case studies for practical insights.– Workshops & Role-Play: Participate in immersive, scenario-based activities.– Practical Application: Focus on applying theoretical knowledge in real situations.– Post-Training Support: Receive extensive support after training for skill implementation.

Discuss your requirements

Dates, duration & arrangements

Contact Ratomac to confirm dates, duration, delivery format, entry requirements and any applicable assessment or certification before booking.