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Lean Six Sigma Green Belt Syllabus

Define Phase

Covers project selection, problem framing, Voice of the Customer, and project charter development.

16%
Weight
16
Questions
128
Marks

Problem Definition and Business Case

  • Project charter components: problem statement, goal statement, scope, team, timeline, business case
  • SMART project goals: Specific, Measurable, Achievable, Relevant, Time-bound
  • Linking Six Sigma projects to strategic goals
  • Project selection criteria: financial impact, feasibility, and strategic alignment
  • DMAIC vs DMADV (Design for Six Sigma): when to use each

Voice of the Customer

  • VOC collection methods: surveys, interviews, focus groups, complaint analysis
  • Kano model: basic, performance, and excitement needs
  • CTQ (Critical to Quality) tree: translating customer needs to measurable requirements
  • QFD (Quality Function Deployment) and House of Quality
  • SIPOC diagram: Suppliers, Inputs, Process, Outputs, Customers

Lean Fundamentals

  • Five Lean principles: value, value stream, flow, pull, perfection
  • Eight wastes (TIMWOODS): Transport, Inventory, Motion, Waiting, Over-processing, Overproduction, Defects, Skills
  • Value-added vs non-value-added activities
  • Value stream mapping (VSM): current state and future state maps
  • Process cycle efficiency: value-added time / total lead time

Measure Phase

Covers data collection, measurement system analysis, process capability, and establishing a baseline.

20%
Weight
20
Questions
160
Marks

Data Types and Collection

  • Variable (continuous) vs attribute (discrete) data
  • Data collection plan: who collects, how, when, and where
  • Sampling methods: random, stratified, systematic
  • Check sheets, Pareto charts, and histograms for initial data summary
  • Operational definitions: defining what you are measuring precisely

Measurement System Analysis (MSA)

  • Gauge R&R (Repeatability and Reproducibility): assessing measurement variation
  • Bias, stability, linearity, and resolution in measurement systems
  • %R&R < 10%: acceptable; 10–30%: may be acceptable; >30%: unacceptable
  • Attribute MSA: Kappa statistic for categorical agreement
  • Sources of measurement error and how to reduce them

Capability Metrics

  • Process capability indices: Cp, Cpk, Pp, Ppk
  • Cp: potential capability (centred process); Cpk: actual capability (includes mean shift)
  • Six Sigma targets: Cpk ≥ 1.33 (4σ), Cpk ≥ 1.67 (5σ)
  • DPMO (Defects Per Million Opportunities) and sigma level conversion
  • Rolled Throughput Yield (RTY) and First Pass Yield (FPY)
  • Baseline sigma calculation from defect rate

Analyse Phase

Covers root cause analysis, statistical hypothesis testing, regression, and identifying key process inputs (Xs).

24%
Weight
24
Questions
192
Marks

Root Cause Tools

  • Cause-and-effect (fishbone / Ishikawa) diagram: 6M categories
  • 5 Whys technique: iterative questioning to root cause
  • Fault tree analysis (FTA): top-down failure analysis
  • Failure Mode and Effects Analysis (FMEA): RPN = Severity × Occurrence × Detection
  • Affinity diagrams and interrelationship digraphs

Hypothesis Testing

  • Null hypothesis (H₀) vs alternative hypothesis (H₁)
  • Type I error (α, false positive) and Type II error (β, false negative)
  • p-value interpretation: p < α → reject H₀
  • t-tests: one-sample, two-sample (independent), and paired t-test
  • ANOVA: comparing means across more than two groups
  • Chi-square test: testing independence of categorical variables

Correlation and Regression

  • Pearson correlation coefficient (r): strength and direction of linear relationship
  • Simple linear regression: equation, R², and residual analysis
  • Multiple regression: interpreting coefficients and interaction terms
  • Scatter plots and identifying outliers and influential points
  • Regression assumptions: linearity, normality of residuals, homoscedasticity

Non-Parametric and Other Tests

  • When to use non-parametric tests: non-normal data, small samples
  • Mann-Whitney U test: non-parametric alternative to two-sample t-test
  • Kruskal-Wallis test: non-parametric alternative to one-way ANOVA
  • Box plots and normal probability plots for distribution assessment

Improve Phase

Covers generating solutions, Design of Experiments (DOE), Lean flow improvement, and pilot testing.

24%
Weight
24
Questions
192
Marks

Idea Generation and Prioritisation

  • Brainstorming and brainwriting for solution generation
  • Solution selection matrix: weighting criteria and scoring
  • Pugh concept selection matrix
  • Poka-yoke (mistake proofing): prevention vs detection controls
  • Kaizen events: rapid improvement workshops

DOE Fundamentals

  • Full factorial designs: 2k designs, main effects, and interaction effects
  • Fractional factorial designs: resolution and confounding
  • Response Surface Methodology (RSM): optimising factor levels
  • Taguchi methods: robust design and noise factors
  • Interpreting main effects plots, interaction plots, and Pareto of effects

Flow and Pull Implementation

  • Single-piece flow vs batch processing
  • Kanban systems: pull signals, card types, and WIP limits
  • 5S methodology: Sort, Set in order, Shine, Standardise, Sustain
  • Total Productive Maintenance (TPM) and OEE (Overall Equipment Effectiveness)
  • Cycle time, takt time, and bottleneck identification

Control Phase

Covers Statistical Process Control (SPC), control charts, response plans, and sustaining improvement.

16%
Weight
16
Questions
128
Marks

Control Charts

  • Control chart types: X-bar and R, X-bar and S, I-MR, p, np, c, u charts
  • Variable vs attribute charts: when to use each
  • Control limits vs specification limits: critical distinction
  • Western Electric rules for detecting special cause variation
  • Common cause vs special cause variation: responding appropriately
  • Out-of-control signals: points beyond control limits, runs, trends

Control Documentation

  • Control plan: process name, input/output, specification, measurement, sample size, frequency, reaction plan
  • Standard operating procedures (SOPs) and work instructions
  • FMEA update post-improvement: revised RPN scores
  • Visual management: dashboards, displays, and standard work
  • Knowledge transfer and training plan for sustainment

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Learning Progress

Define Phase 85%
Measure Phase 92%

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