Black Belt Body of Knowledge

Introduction

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

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, current and future state
• Takt and Flow
• 5S
• Quick changeover
• Total productive maintenance

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, Gantt charts, lessons learned
• Gate reviews

Basic Statistics

• Variation, sample, population, distribution, mean, median, mode, range, standard deviation, variance
• Descriptive and inferential statistics
• Normal and non-normal data, Anderson-Darling normality test
• Data transformations
• 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

• Selecting and defining output characteristics and performance standards       
• Detailed process mapping
• Project charter, problem statements
• Project scope, goals, objectives, and performance measures

Measure Phase

• Validate the measuring system
• Attribute agreement analysis and variable gage R & R
• Establish current process capability
• Measurement methods
• Data collection, sampling methods, types of data, sample size
• Process performance vs. specifications
• Attribute and variable process capability
• Evaluating project objectives

Analyze Phase

• Identifying and screening 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
• Failure modes and effects analysis (FMEA)
• Hypothesis testing
• Significance level, power, resolution, alpha and beta error
• 1-proportion, 2-proportion, and Chi square tests
• 1-sample t, 2-sample t, ANOVA tests
• Paired t test
• Test for equal variances
• Correlation
• Regression and multiple regression
• Binary logistic regression
• Nonparametric testing
• Design of experiments (DOE), full factorial designs, fractional factorial designs

Improve Phase

• Developing solutions and targeting critical inputs
• Solution matrices and action plans
• Managing change
• Re-evaluating the measuring system
• Implementing and establishing final capability
• Improvement verification and Pilot Studies
• Modeling improvements

Control Phase

• Implementing process controls and control plans
• Mistake proofing
• Internal audits and ongoing evaluation
• SPC for control
• Calculating financial benefits, ROI, soft vs. hard project benefits
• Project closure, leveraging benefits, and team recognition
• Sustaining the gains