QCLSSC Lean Six Sigma Green Belt Level 2 Certification

Module 1: What Is Six Sigma?

• Understand the fundamentals of Six Sigma methodology and its role in process improvement.
• Recognize the impact of Six Sigma on operational efficiency, quality management, and business performance.

Module 2: Six Sigma History and Application

• Explore the evolution of Six Sigma and its adoption across global industries.
• Identify practical applications in manufacturing, service, and process optimization projects.

Module 3: Other Process Improvement and Quality Methods

• Learn complementary quality improvement tools like Total Quality Management (TQM) and Kaizen.
• Understand how Lean and Six Sigma integrate for continuous improvement initiatives.

Module 4: Lean Concepts

• Apply Lean principles to reduce waste, enhance workflow efficiency, and maximize value.
• Understand value stream mapping and process flow optimization for business excellence.

Module 5: Basic Six Sigma Concepts

• Develop foundational knowledge of variation, defects, and process capability.
• Understand key metrics used to measure quality and operational performance.

Module 6: Approaching the Problem

• Identify root causes of inefficiencies using structured problem-solving techniques.
• Apply process thinking to define actionable improvement strategies.

Module 7: What is a Process?

• Define processes within operational and business contexts.
• Map workflows to identify bottlenecks and areas for improvement.

Module 8: Quality

• Understand quality standards and metrics for customer satisfaction and compliance.
• Learn techniques to monitor, control, and enhance product or service quality.

Module 9: Selecting the Right Projects

• Identify high-impact process improvement projects aligned with organizational goals.
• Prioritize initiatives using strategic decision-making and ROI analysis.

Module 10: Basic Six Sigma Team Management

• Develop skills to lead cross-functional Six Sigma project teams.
• Enhance collaboration and accountability in quality improvement initiatives.

Module 11: Introduction to DMAIC and DMADV

• Understand DMAIC (Define, Measure, Analyze, Improve, Control) and DMADV frameworks.
• Apply structured methodologies to optimize processes and design new processes effectively.

Module 12: Define

• Clearly define project goals, scope, and customer requirements.
• Create problem statements and project charters for effective process improvement.

Module 13: Measure

• Collect and analyze data to establish baseline process performance.
• Identify key performance indicators (KPIs) and measurement techniques for Six Sigma projects.

Module 14: Analyze

• Perform root cause analysis using statistical and problem-solving tools.
• Identify patterns, trends, and areas for process enhancement.

Module 15: Improve

• Develop and implement effective solutions to reduce defects and inefficiencies.
• Apply Lean tools to enhance productivity, reduce waste, and improve workflows.

Module 16: Control

• Establish monitoring systems to sustain process improvements.
• Implement control charts, standard operating procedures, and continuous improvement plans.

Module 17: Intermediate Graphical Analysis

• Visualize process data using charts, histograms, and Pareto analysis.
• Interpret graphs to support data-driven decision-making in process optimization.

Module 18: Normal Probability Distributions

• Apply normal distribution concepts to assess process variation and quality performance.
• Use statistical tools to model and predict outcomes in operational processes.

Module 19: Correlation and Regression

• Analyze relationships between variables to identify influences on process performance.
• Apply regression models to forecast outcomes and guide improvement initiatives.

Module 20: Non-Normal Probability Distributions

• Recognize non-normal data patterns and apply appropriate statistical techniques.
• Understand how to handle skewed or complex process data in quality projects.

Module 21: Hypothesis Testing

• Conduct hypothesis testing to validate process improvement strategies.
• Make evidence-based decisions to ensure statistically significant results.

Module 22: Sample Size

• Determine appropriate sample sizes for data collection and analysis.
• Ensure accurate and reliable results for process improvement projects.

Module 23: Advanced Control Charts

• Use control charts to monitor process stability and performance trends.
• Identify variations and take corrective actions to maintain process consistency.

Module 24: Applying Statistics to Business Applications Through Six Sigma

• Translate statistical analysis into actionable business insights.
• Apply Six Sigma tools and Lean principles to optimize operations, reduce costs, and improve quality.