Duration 7 Days – 49 hrs.

 

Overview

This comprehensive Lean Six Sigma Green Belt Training Course equips participants with the knowledge and practical tools to improve business processes, reduce waste, control variation, solve operational problems, and deliver measurable results.

 

The course follows the Define–Measure–Analyze–Improve–Control (DMAIC) methodology and integrates Lean principles, process analysis, root-cause analysis, statistical techniques, risk assessment, solution development, and process control. Participants will learn to identify suitable improvement opportunities, understand customer and business requirements, measure current performance, validate root causes, implement effective solutions, and sustain process improvements.

 

Hands-on exercises using Microsoft Excel enable participants to analyze process data and apply Green Belt tools in manufacturing, service, administrative, transactional, and operational environments.

 

Objectives 

• Explain Lean Six Sigma principles and the DMAIC improvement methodology
• Identify and prioritize appropriate Lean Six Sigma projects
• Translate customer and business requirements into measurable performance requirements
• Develop a clear project charter and define project scope, objectives, stakeholders, and governance
• Map and analyze end-to-end processes using SIPOC, process maps, and value stream mapping
• Distinguish value-added activities from non-value-added activities
• Identify the effects of waste, unevenness, and overburden on process performance
• Develop operational definitions, data-collection plans, and appropriate sampling approaches
• Assess measurement reliability using measurement system analysis
• Calculate and interpret baseline performance, process capability, yield, and process cycle efficiency
• Use charts and basic statistical tools to analyze process behavior and variation
• Identify, prioritize, and validate potential root causes
• Apply hypothesis testing, correlation, scatter plots, and regression analysis appropriately
• Evaluate process risks and failure modes using Process FMEA
• Generate, assess, and pilot practical improvement solutions
• Apply Lean improvement techniques such as 5S, standard work, mistake-proofing, and SMED
• Use basic Design of Experiments concepts to evaluate process factors and optimize solutions
• Develop control plans, control charts, reaction plans, and standard operating procedures
• Track project benefits and prepare a Lean Six Sigma project storyboard

 

Target Audience 

• Process Improvement Specialists
• Quality Assurance and Quality Control Professionals
• Engineers and Technical Specialists
• Operations Managers and Supervisors
• Production and Manufacturing Personnel
• Business Process Analysts
• Project Managers and Project Team Members
• Continuous Improvement and Operational Excellence Teams
• Supply Chain, Logistics, and Warehouse Professionals
• Customer Service and Shared Services Personnel
• Finance, Human Resources, IT, and Administrative Professionals
• Employees expected to lead or participate in process improvement projects
• Professionals preparing for Lean Six Sigma Green Belt responsibilities

 

Prerequisites 

• Basic knowledge of workplace or business processes
• Basic proficiency in Microsoft Excel
• Familiarity with simple mathematical concepts such as percentages and averages
• Access to Microsoft Excel with the Data Analysis ToolPak enabled
• A potential workplace process or improvement opportunity for practical application
• Previous Lean Six Sigma experience is not required. Completion of Yellow Belt training is helpful but not mandatory.

 

Course Outline

 

Day 1 – Lean Six Sigma Foundations and Define Phase

Module 1: Introduction to Lean Six Sigma

• Overview and evolution of Lean and Six Sigma
• Lean versus Six Sigma
• Benefits of an integrated Lean Six Sigma approach
• Process improvement and variation reduction
• Roles and responsibilities within Lean Six Sigma
• Green Belt responsibilities and competencies

 

Module 2: Understanding the DMAIC Roadmap 

• Define, Measure, Analyze, Improve, and Control
• Purpose and expected outputs of each phase
• DMAIC project structure and decision gates
• Linking improvement projects to organizational goals

 

Module 3: Project Identification and Prioritization 

• Sources of Lean Six Sigma projects
• Voice of the Customer
• Voice of the Business
• Identifying customer and business requirements
• Project selection criteria
• Project prioritization
• Assessing project feasibility and potential benefits
• Stakeholder analysis
• Project governance and sponsorship

 

 

 Day 2 – Define Phase and Process Understanding

Module 4: Developing the Project Charter 

• Business case
• Problem statement
• Goal statement
• Project scope and boundaries
• Project deliverables
• Project milestones and timeline
• Project team and responsibilities
• Risks, assumptions, and constraints

 

Module 5: High-Level Process Definition 

• Understanding the end-to-end process
• Defining process start and end points
• Identifying customers and suppliers
• Identifying process inputs and outputs
• SIPOC diagram development
• High-level process mapping

 

Module 6: Understanding Customer Requirements 

• Voice of the Customer collection methods
• Converting customer needs into measurable requirements
• Critical-to-Quality characteristics
• Kano Model
• Basic, performance, and excitement requirements
• Identification of Key Process Output Variables
• Identification of Key Process Input Variables

 

 

Day 3 – Lean Process Analysis and Value Stream Mapping

Module 7: Lean Thinking and Process Value 

• Lean principles
• Customer-defined value
• Value-added, business-value-added, and non-value-added activities
• Understanding process flow
• Identifying opportunities for waste elimination

 

Module 8: Waste, Unevenness, and Overburden 

• Muda: process waste
• TIMWOODS waste categories
• Transportation
• Inventory
• Motion
• Waiting
• Overproduction
• Overprocessing
• Defects
• Skills or underutilized talent
• Mura: unevenness
• Muri: overburden

 

Module 9: Value Stream and Flow Analysis 

• Value stream mapping
• Material and information flow
• Current-state mapping
• Lead-time analysis
• Cycle time
• Takt time
• Process Cycle Efficiency
• Spaghetti diagram
• Workplace movement analysis
• Identifying bottlenecks and improvement opportunities
• Microsoft Excel applications for Lean process analysis

 

 

Day 4 – Measure Phase and Process Capability

Module 10: Data Collection and Measurement 

• Purpose of the Measure phase
• Data types and data sources
• Continuous and discrete data
• Operational definitions
• Data-collection planning
• Sampling principles and methods
• Data accuracy and integrity

 

Module 11: Measurement System Analysis 

• Understanding measurement error
• Accuracy, precision, repeatability, and reproducibility
• Gage Repeatability and Reproducibility
• Attribute Agreement Analysis
• Evaluating measurement system reliability

 

Module 12: Descriptive Statistics and Data Visualization 

• Mean, median, and mode
• Range and standard deviation
• Run charts
• Histograms
• Pareto charts
• Scatter plots
• Introduction to linear regression
• Using Microsoft Excel Data Analysis tools

 

Module 13: Baseline Performance and Capability 

• Understanding process variation
• Process stability
• Common-cause and special-cause variation
• Process capability concepts
• First Pass Yield
• Rolled Throughput Yield
• Process Cycle Efficiency
• Establishing the current-state performance baseline

 

  

Day 5 – Analyze Phase and Root-Cause Validation

Module 14: Root-Cause Analysis 

• Moving from symptoms to root causes
• Fishbone or cause-and-effect diagram
• 5 Whys analysis
• Cause-and-Effect Matrix
• Prioritizing potential causes
• Bottleneck analysis
• Linking root causes to KPOVs and KPIVs

 

Module 15: Statistical Analysis and Cause Validation 

• Introduction to statistical inference
• Formulating null and alternative hypotheses
• Understanding significance levels and p-values
• Parametric and non-parametric data
• Selecting an appropriate hypothesis test
• Interpreting test results
• Scatter plot interpretation
• Correlation and linear regression
• Validating root causes using data
• Statistical analysis using Microsoft Excel

 

 

Day 6 – Analyze, Risk Analysis, and Improve Phase

Module 16: Solution Generation and Selection 

• Translating validated causes into solutions
• Creative solution generation
• SCAMPER technique
• Brainstorming and solution development
• Impact–Effort Matrix
• Evaluating feasibility, benefits, costs, and risks
• Selecting appropriate improvement solutions

 

 Module 17: Lean Improvement Techniques 

• 5S workplace organization
• Conducting a 5S audit
• Mistake-proofing or Poka-Yoke
• Standard work
• Single-Minute Exchange of Die
• Reducing setup and changeover time
• Improving workflow and reducing non-value-added activities

 

Module 18: Process Risk Analysis and Pilot Implementation 

• Introduction to Process Failure Mode and Effects Analysis
• Identifying potential failure modes
• Assessing effects, causes, and existing controls
• Evaluating severity, occurrence, and detection
• Prioritizing process risks
• Developing corrective and preventive actions
• Preparing a pilot plan
• Defining pilot measures and success criteria
• Evaluating pilot results

 

 

Day 7 – Improve, Design of Experiments, and Control Phase

Module 19: Process Optimization and Experimentation 

• Introduction to Design of Experiments
• Factors, levels, responses, and interactions
• Structured experimentation principles
• Comparing controlled experiments with trial-and-error approaches
• Using experiments to identify optimal process settings
• Interpreting experimental results
• Confirming improvement outcomes

 

Module 20: Statistical Process Control 

• Purpose of Statistical Process Control
• Understanding control limits
• Control limits versus specification limits
• Introduction to control charts
• Selecting an appropriate control chart
• Identifying common-cause and special-cause variation
• Interpreting control-chart patterns
• Establishing a reaction plan
• Using Microsoft Excel for process monitoring

 

Module 21: Sustaining and Standardizing Improvements 

• Developing a process control plan
• Defining control measures and responsibilities
• Standard operating procedures
• Standard work documentation
• Visual management
• Monitoring process performance
• Preventing process regression
• Transferring ownership to the process owner

 

Module 22: Benefits Tracking and Project Closure 

• Validating financial and operational benefits
• Tracking tangible and intangible improvements
• Comparing results against the project baseline
• Preparing a Lean Six Sigma project storyboard
• Documenting lessons learned
• Project handover and closure
• Opportunities for continuous improvement

 

Important note: Completion of the seven-day training may support a participant’s Green Belt development. Formal Green Belt certification should normally require successful completion of an examination and/or an approved workplace improvement project, depending on the certifying organization’s requirements.