Six Sigma Green Belt Training

Program Overview

The Six Sigma Green Belt program provides a comprehensive framework for individuals to lead and support process improvement initiatives using a data-driven approach. Following the structured DMAIC (Define, Measure, Analyze, Improve, Control) methodology, the course equips participants with the skills to identify opportunities, objectively analyze problems, implement validated solutions, and sustain long-term gains.

Key areas of focus include understanding the Voice of the Customer and translating it into Critical-to-Quality (CTQ) metrics, quantifying the financial impact of quality (Cost of Quality), and rigorously defining project scopes.

A strong emphasis is placed on the “Measure” phase, ensuring data accuracy through Measurement System Analysis (MSA) and understanding baseline performance.

In the “Analyze” phase, statistical tools and hypothesis testing are extensively covered to identify root causes and sources of variation within processes.

The “Improve” phase concentrates on developing and validating effective solutions, leveraging techniques like correlation and regression.

Finally, the “Control” phase focuses on establishing comprehensive monitoring systems using Statistical Process Control (SPC) charts and implementing comprehensive control plans to prevent regression and ensure sustained performance.

This curriculum integrates practical application of statistical software, and reinforces the critical thinking required to drive continuous improvement in various business environments. Practical learning is cemented through a mandatory in-class group project where participants apply the DMAIC methodology to a real-world scenario.

Intended Audience

Process Improvement Team Members: Analysts, Engineers, Specialists, and Project Managers who need to lead smaller projects or support Black Belts on larger ones.

Department Managers and Supervisors: Leaders responsible for improving the efficiency, quality, and effectiveness of processes within their own teams.

Quality and Continuous Improvement Professionals: Those working in Quality Assurance, Operational Excellence, or seeking to formalize their data-driven problem-solving skills.

Aspiring Leaders: Professionals looking to develop a foundational, data-driven methodology (DMAIC) for tackling business problems and driving measurable results.

Course Topics

1. SIX SIGMA AND DMAIC METHODOLOGY
   This section introduces you to the core principles of Six Sigma and the foundational DMAIC (Define, Measure, Analyze, Improve, Control) methodology. You’ll learn how Six Sigma drives process improvement by focusing on customer requirements and using data to identify and solve problems. You’ll also learn to define the scope of a project and establish initial performance metrics.
2. MEASUREMENT AND DATA ANALYSIS FUNDAMENTALS
   This topic dives into the Measure and Analyze phases. You’ll learn how to evaluate the accuracy of your data using Measurement System Analysis (MSA) and establish a baseline of process performance. The course covers key statistical concepts and tools for collecting, displaying, and analyzing data to identify sources of variation.
3. PROCESS IMPROVEMENT AND CONTROL
   In the Improve and Control phases, you’ll learn to develop and implement effective solutions to address the root causes you’ve identified. This includes using tools like correlation and regression to validate solutions. You will also learn how to create a control plan and use Statistical Process Control (SPC) charts to monitor the process and ensure long-term gains are sustained.
4. COST OF QUALITY AND PROJECT DEFINITION
   We explore the financial side of quality, breaking down how poor quality impacts an organization’s bottom line. You’ll learn how to quantify the cost of quality and use this knowledge to define viable Six Sigma projects. We’ll cover how to determine a project’s feasibility based on data availability, statistical tool applicability, and business impact.
5. STATISTICAL INFERENCE AND HYPOTHESIS TESTING
   This section focuses on using inferential statistics to draw reliable conclusions about an entire population from a smaller sample of data. You’ll be introduced to various statistical distributions and learn how to apply different hypothesis tests to compare means, variances, and proportions, enabling you to make data-driven decisions with confidence
6. IN-CLASS GROUP PROJECT
   Practical learning is cemented through a mandatory in-class group project where participants apply the DMAIC methodology to a real-world scenario.

Cost & Registration

• Price: $2,500 for single registration.
• Registration fees include breakfast, lunch, and all course materials for each training session.