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 

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
  • M2: Establish current process capability
    • Measurement methods
    • Data collection, sampling methods, types of data
    • Process performance verses specifications
    • Attribute and variable process capability
  • 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
  • A3: Determine the f(x)
    • One-factor-at-a-time experiment
    • Overview of correlation, regression, and DOE

Improve Phase

  • I1: Establish operating tolerances
    • Solution matrices
    • Managing change
  • I2: Re-evaluate the measuring system
  • I3: Establish final capability
    • Pilot study

Control Phase

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

 

NIST

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