Lean Six Sigma Black Belt Advanced Methods

Programme Summary

Extend established Green Belt capability into advanced analytical methods and complex improvement leadership. Participants evaluate multivariable problems, experimental designs and difficult data conditions through a demanding project case. The programme strengthens model judgement, risk awareness and evidence based recommendations; it assumes prior statistical competence and does not replace the workplace experience or project evidence required for independent professional certification.

Training Objectives

1 Deepen advanced statistical improvement judgement; 2 Select methods for complex process problems; 3 Strengthen experiment design and model validation; 4 Lead evidence based cross functional decisions; 5 Plan sustainable controls for significant improvements.

Learning Outcomes

1 Select advanced analysis for a project; 2 Interpret multivariable model diagnostics accurately; 3 Design a justified factorial experiment; 4 Evaluate improvement evidence and residual risks; 5 Defend a complete technical project recommendation.

Target Audience

Senior Improvement Specialists; Experienced Green Belts; Process Excellence Managers; Quality Engineering Leads; Operational Excellence Leaders.

Target Industries

Automotive Manufacturing; Electronics Manufacturing; Pharmaceutical Manufacturing; Financial Operations; Industrial Services; Healthcare Operations.

Course Contents

• Module 1 Advanced Improvement Leadership: Project selection and strategic alignment; Complex stakeholder and process interfaces; Evidence standards and ethical decision making.
• Module 2 Project Definition and Value: Problem framing and benefit hypotheses; Financial assumptions and benefit verification; Scope control and phase review decisions.
• Module 3 Measurement Strategy Review: Critical measures and operational definitions; Measurement capability and sampling risks; Data lineage and missing data treatment.
• Module 4 Probability and Distribution Selection: Distribution assumptions and practical interpretation; Non normal data and transformations; Tail behaviour and decision implications.
• Module 5 Advanced Hypothesis Testing: Test selection and practical significance; Power sample size and confidence intervals; Multiple comparisons and error control.
• Module 6 Analysis of Variance: Fixed effects and experimental structure; Interactions blocking and residual checks; Comparisons supported by model assumptions.
• Module 7 Multiple Regression: Predictor selection and model interpretation; Collinearity residuals and influential observations; Validation and prediction limitations.
• Module 8 Binary Response Models: Binary outcomes and logistic model concepts; Odds probabilities and model fit; Classification thresholds and decision costs.
• Module 9 Nonparametric Methods: Rank based tests and assumptions; Paired independent and ordered observations; Interpreting findings without unsupported claims.
• Module 10 Time Dependent Data: Autocorrelation and time sequence effects; Separating trends shifts and seasonality; Limits of independent observation methods.
• Module 11 Experiment Strategy: Objectives factors responses and constraints; Randomisation replication and blocking; Safe experimentation and resource planning.
• Module 12 Full Factorial Experiments: Main effects and interaction interpretation; Design matrices and run order; Model adequacy and confirmation runs.
• Module 13 Fractional Factorial Experiments: Confounding aliasing and design resolution; Screening tradeoffs and sequential learning; Follow up experiments and interpretation limits.
• Module 14 Optimisation Approaches: Curvature and response surface concepts; Multiple response tradeoffs and constraints; Robustness checks and operating windows.
• Module 15 Advanced Process Risk: Failure mechanisms and control interactions; Risk reduction before implementation; Verification of unintended consequences.
• Module 16 Reliability and Time to Event Data: Censoring failure definitions and exposure; Interpreting survival and life distributions; Limits of accelerated test extrapolation.
• Module 17 Capability and Monitoring Strategy: Distribution and stability suitability checks; Advanced monitoring and subgroup decisions; Avoiding overstatement of process performance.
• Module 18 Change and Benefit Realisation: Implementation ownership and stakeholder adoption; Benefit validation against reliable baselines; Sustainment risks and project closure evidence.
• Module 19 Technical Review and Coaching: Challenging assumptions and analytical shortcuts; Explaining uncertainty to decision makers; Coaching teams through evidence reviews.
• Module 20 Advanced Project Defence: Integrating analyses into justified recommendations; Defending model assumptions and limitations; Presenting control and benefit verification plans.

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 reference pack and calculator permitted; external internet and AI prohibited.
• Individual applied assessment (90 minutes): Analyse a supplied complex project dataset, select and defend statistical methods, interpret an experiment and present a risk controlled improvement recommendation.
• Assessment criteria: Appropriate advanced method selection; Correct interpretation and assumption checks; Defensible implementation and control judgement.
• Pass each component separately: 75/100 written marks (75%) and at least 70% on the applied task.
• 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 advanced Black Belt method learning; course completion alone does not establish independent Black Belt certification or workplace project competence.
• 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

Green Belt level knowledge, completed improvement project experience and working competence in hypothesis testing, regression and statistical software are required.Green Belt level knowledge, completed improvement project experience and working competence in hypothesis testing, regression and statistical software are required.Green Belt level knowledge, completed improvement project experience and working competence in hypothesis testing, regression and statistical software are required.

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

Complete a 45-minute advanced statistics diagnostic and review a supplied project dataset before attendance.Complete a 45-minute advanced statistics diagnostic and review a supplied project dataset before attendance.Complete a 45-minute advanced statistics diagnostic and review a supplied project dataset before attendance.

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.75% written and 70% applied, passed separately; full attendance.75% written and 70% applied, passed separately; full attendance.