Green Belt Body of Knowledge

Introduction

• Six Sigma history and terminology
• The DMAIC process
• Processes, inputs, and outputs
• Six Sigma roles and responsibilities

Project Selection

• Project selection criteria
• Identifying internal metrics
• Voice of the customer: SIPOC, VOC plans, affinity diagrams, Kano analysis, critical-to-satisfaction (CTS) characteristics
• Sample projects

Lean Enterprise

• Introduction to lean tools and eight wastes
• Value stream mapping

Team Building

• Roles and responsibilities
• Ingredients for successful teams
• Communication and feedback

Project Management

• Project life cycle
• Project team and stakeholders
• Project management tools: Scope statement, work breakdown structure, risk register, action items log, lessons learned

Basic Statistics

• Terms: Variation, sample, population, distribution, mean, median, mode, range, standard deviation, variance
• Descriptive and inferential statistics
• Normal and non-normal data, Anderson-Darling normality test
• Graphic methods: Histograms, Pareto charts, scatter diagrams
• Variable and attribute data
• Run charts and control charts: I-MR, X-bar and R, P, and U
• Special and common cause variation
• Control chart analysis 
• Basic statistics in Minitab 

Define Phase

• D1: Select an output characteristic
• D2: Define output performance standard
• D3: Describe the process
  • Output characteristics
  • Detailed process mapping
  • Project charter, problem statements
  • Project scope, goals, objectives, and performance measures

Measure Phase

• M1: Validate the measuring system
  • Attribute agreement analysis and variable gage R & R
  • Minitab exercises 
• M2: Establish current process capability
  • Measurement methods
  • Data collection, sampling methods, types of data
  • Process performance verses specifications
  • Attribute and variable process capability
  • Minitab exercises 
• M3: Determine project objectives

Analyze Phase

• A1 and A2: Identify and screen potential causes
  • Root cause analysis
  • Brainstorming, cause and effect (fishbone) diagram, five-why analysis, is/is not analysis
  • List reduction, risk frequency grid, cause and effect matrix, and potential X matrix
  • Minitab exercises
• A3: Determine the f(x)
  • One-factor-at-a-time experiment
  • Overview of correlation, regression, and DOE
  • Minitab exercises 

Improve Phase

• I1: Develop solution(s)
  
  • Solution matrices
  • Managing change
• I2: Re-evaluate the measuring system
• I3: Implement and establish final capability
  
  • Pilot study

Control Phase

• C1: Implement process controls
  • Control plans
  • Mistake proofing
  • Internal audits
  • Lessons learned
  • Ongoing evaluation