QCLSSC Lean Six Sigma Black Belt Level 2 Certification

Module 1: Introduction to Six Sigma

• Understand the fundamentals of Six Sigma and process improvement methodology
• Explore the role of Black Belt professionals in continuous improvement projects

Module 2: Six Sigma History and Practical Applications

• Review historical evolution of Six Sigma
• Identify real-world quality management applications

Module 3: Process Improvement and Quality Methodologies

• Analyze lean process techniques
• Apply tools for organizational efficiency and operational excellence

Module 4: Lean Principles and Concepts

• Learn Lean thinking and waste reduction strategies
• Apply continuous improvement principles in business operations

Module 5: Core Six Sigma Concepts

• Develop understanding of key Six Sigma tools
• Master statistical process control and variation reduction

Module 6: Structured Problem-Solving Approaches

• Implement systematic problem-solving methods
• Use root cause analysis to resolve process inefficiencies

Module 7: Understanding Business Processes

• Map and analyze workflows for performance optimization
• Improve operational efficiency across departments

Module 8: Quality Fundamentals

• Understand quality metrics and process capability measurement
• Apply quality improvement techniques aligned with business goals

Module 9: Project Selection and Prioritization

• Identify projects with high business impact
• Use structured frameworks to prioritize Lean Six Sigma projects

Module 10: Six Sigma Team Roles and Collaboration

• Understand responsibilities within cross-functional project teams
• Develop collaboration and leadership skills

Module 11: Introduction to DMAIC and DMADV

• Apply DMAIC for process improvement and DMADV for process design.
• Understand each phase's objectives, deliverables, and analytical tools.
• Gain practical knowledge for real-world Six Sigma implementation.

Module 12: Define Phase

• Define project scope, objectives, and customer requirements.
• Develop clear problem statements and project charters.
• Identify key performance indicators (KPIs) for measurement.

Module 13: Measure Phase

• Collect reliable data to establish process baselines.
• Measure process performance and identify gaps.
• Apply measurement systems analysis for data accuracy.

Module 14: Analyze Phase

• Analyze process data to identify root causes of defects.
• Apply statistical tools to detect variation and inefficiencies.
• Use data-driven insights to inform improvement strategies.

Module 15: Improve Phase

• Develop and implement solutions to optimize processes.
• Apply Lean tools to eliminate waste and enhance efficiency.
• Validate improvements through pilot testing and performance tracking.

Module 16: Control Phase

• Implement control plans to sustain process improvements.
• Monitor KPIs and establish performance tracking systems.
• Ensure compliance with organizational and industry quality standards.

Module 17: Intermediate Graphical Data Analysis

• Interpret charts, graphs, and visual data representations.
• Use statistical visualization to support decision-making.
• Identify trends, patterns, and anomalies for process optimization.

Module 18: Normal Probability Distributions

• Understand and apply normal distribution concepts in quality analysis.
• Calculate probabilities, confidence intervals, and performance metrics.
• Use statistical knowledge to support Six Sigma projects.

Module 19: Correlation and Regression Analysis

• Analyze relationships between process variables.
• Apply regression techniques for predictive process improvement.
• Support data-driven decision-making and operational insights.

Module 20: Non-Normal Probability Distributions

• Understand and analyze non-normal process data.
• Apply appropriate statistical techniques for irregular datasets.
• Improve problem-solving in real-world process scenarios.

Module 21: Hypothesis Testing Fundamentals

• Perform hypothesis testing to validate improvement assumptions.
• Make evidence-based decisions for process changes.
• Apply statistical tests to enhance quality and performance.

Module 22: Sample Size and Data Reliability

• Determine optimal sample sizes for reliable analysis.
• Ensure accuracy and confidence in collected process data.
• Apply statistical sampling for Lean Six Sigma projects.

Module 23: Advanced Control Charts

• Design and interpret control charts for process monitoring.
• Detect variations and take corrective actions proactively.
• Enhance quality control and operational efficiency.

Module 24: Applying Statistics to Business Through Six Sigma

• Apply statistical analysis to solve business problems.
• Integrate data-driven insights into continuous improvement initiatives.
• Use statistical tools to support process excellence and efficiency.

Module 25: Introduction to Minitab

• Navigate Minitab for Six Sigma data analysis.
• Perform basic statistical functions to support improvement projects.
• Gain practical skills for real-world process measurement.

Module 26: Graphs and Quality Tools in Minitab

• Create histograms, Pareto charts, and scatter plots.
• Use Minitab to visualize process performance.
• Apply quality tools for problem-solving and data interpretation.

Module 27: Statistical Analysis Using the Minitab Stat Menu

• Conduct t-tests, ANOVA, and regression analysis in Minitab.
• Interpret statistical outputs for informed decision-making.
• Support Lean Six Sigma projects with robust data analysis.

Module 28: Analysis of Variance (One-Way ANOVA)

• Compare multiple process means to identify significant differences.
• Use ANOVA for process improvement and variation reduction.
• Apply findings to enhance operational performance.

Module 29: Design of Experiments (DOE)

• Plan experiments to test process changes effectively.
• Optimize processes using controlled experimentation.
• Analyze results for continuous improvement initiatives.

Module 30: Advanced DOE and Factorial Experiments

• Implement factorial designs for complex process analysis.
• Evaluate multiple variables simultaneously for optimization.
• Support Lean Six Sigma project decisions with experimental data.

Module 31: Brainstorming and Process Improvement Tools

• Use brainstorming techniques to generate improvement ideas.
• Apply Kaizen, SIPOC, and other Lean tools to enhance processes.
• Facilitate collaborative problem-solving and team engagement.

Module 32: Process Mapping Techniques

• Develop detailed process maps to visualize workflows.
• Identify bottlenecks, redundancies, and inefficiencies.
• Use mapping insights to drive Lean Six Sigma improvements.

Module 33: Value Stream Mapping

• Analyze the end-to-end flow of materials and information.
• Identify value-adding and non-value-adding activities.
• Optimize processes to enhance productivity, reduce waste, and improve quality.

Key Benefits

By the end of this course, you will be able to:

• Earn a globally recognized Black Belt certification
• Apply Lean Six Sigma tools and techniques immediately in the workplace
• Drive measurable business performance improvements
• Build competence in data analysis, risk management, and quality improvement
• Enhance ability to lead strategic operational initiatives