Black Belt Body of Knowledge

  • Introduction
    • Six sigma history and terminology
    • Define-Measure-Analyze-Improve-Control (DMAIC) methodology
    • Processes, inputs and outputs
    • Six sigma roles and responsibilities
    • Theory of constraints
    • Introduction to lean
    • Integration of six sigma and lean
    • Manufacturing and service six sigma and lean applications- examples of projects
  • Project selection
    • Project selection criteria
    • Internal metrics: parts per million, defects per million opportunities, rolled through quality
    • Voice of the customer: SIPOC, affinity diagrams, kano diagrams, critical to satisfaction
    • Detailed process map
  • Lean enterprise
    • Introduction to lean– lean tools and eight wastes
    • Value stream mapping
    • 5 S
    • Quick changeover
    • Total Productive Maintenance
  • Team building
    • Roles and responsibilities
    • Four stages: storming, forming, norming and performing
    • Ingredients for successful teams
    • Communication and feedback
  • Basic Statistics
    • Terms: Sample, population, distribution, mean, median, mode, range, standard deviation
    • Descriptive statistics
    • Normal and non-normal data, Anderson-Darling test
    • Graphic methods: Histograms, pareto charts, scatter diagrams
    • Variable and attribute data
    • Run charts and control charts: I-MR, x-bar and R, P, NP, C, and U
    • Special and common cause variation
    • Control chart analysis
    • MINITAB exercises
  • Define Phase
    • D1- Select an output characteristic
    • D2- Define the performance standard
    • D3- Describe the process
      • 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- Identifying and screening potential causes
      • Root cause analysis
      • Brainstorming, list reduction, five why
      • Cause and effect diagrams
      • Cause and effect matrix, family of variation, and potential “X†matrix
      • Process failure and effects analysis (FMEA)
      • Hypothesis testing
      • Terminology: significance level, power, resolution, alpha and beta error
      • 1-proportion, 2-proportion, Chi square
      • 1-sample t, 2-sample t, ANOVA
      • Paired t
      • MINITAB exercises
    • A3- Determining the f(x)
      • One factor at a time experiment
      • Correlation
      • Regression
      • Design of experiments
      • Full factorial design
      • Fractional factorial
      • MINITAB exercises
  • 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 plan
      • Mistake proofing
      • Internal audits
      • Lessons learned
      • Ongoing evaluation
NIST

Manufacturing Extension Partnership, 8626 E. 116th Street, Suite 200, Fishers, IN 46038-2815, (317) 275-6810

© 2017 Purdue University | An equal access/equal opportunity university | Copyright Complaints | Maintained by Manufacturing Extension Partnership

Trouble with this page? Disability-related accessibility issue? Please contact Manufacturing Extension Partnership at tapmep@purdue.edu.