Appendix B: The Six Sigma Body of Knowledge

The following is a list of the Six Sigma body of knowledge. Under the columns marked “Green,” “Black,” and “Master” LSS Belts, the following symbols are used:

  • “A” means they are almost always used. At least 90% of the projects will use these tools. (The related belt must be trained on how to use these tools or already have been trained in the use of these tools.)
  • “O” means often used. It is used in more than 50% of the projects. (The related belt should be trained on how to use these tools or already have been trained on these tools.)
  • “S” means sometimes used. It is used in 25 to 49% of the projects. (The related belt should know what they are used for and know where to go to get more information on how to use them.)
  • “I” means infrequently used to never used. It is used in less than 24% of the projects. (These tools are nice to know but not required and not part of the belt’s training or certification test.)
  LSS Belts
Body of Knowledge Green Black Master
5S’s O O O
5M’s (materials, machines, manpower, methods, measurements) A A A
Acceptance decisions I S S
Activity network diagrams S S S
Affinity diagrams S O O
Area activity analysis (AAA) S I I
Automation I S S
Axiomatic design I S S
Bar charts/graphs A A A
Benchmarking S O O
Bessel function I S O
Binomial distribution O O O
Bivariate distribution I S O
Box plots S O O
Brainstorming A A A
Bureaucracy elimination S O O
Business case development A O O
Business process improvement S O O
Business-value-added S A A
Calibration O O O
Cause-and-effect (fishbone) diagrams O O O
Cause-and-effect matrix O O O
Cellular manufacturing S O O
Central limit theorem O O O
Chi-square distribution O O O
Coefficient of contingency (c) I S S
Collecting data A A A
Communication techniques O O A
Confidence interval for the mean/proportion/variance O O O
Conflict resolution O O O
Continuous flow manufacturing (CFM) S O O
Control charts
X bar–R charts O O O
Run charts O O O
MX bar-MR charts S O O
X-MR charts S O O
X bar–S charts S O O
Median charts I S O
Short-run charts S S O
p-Charts O O O
r-Charts S O O
u-Charts S O O
CuSum control charts I S S
Correlation coefficient O O O
Cp O O O
Cpk O O O
CQFA (cost, quality, features, and availability) S S O
Critical to quality (CTQ) A A A
Critical path method O O O
Culture roadblocks I O O
Cumulative distribution function S O O
Current state mapping O O O
Customer requirements A A A
Customer surveys S O O
Cycle time analysis S O O
Design for maintainability and availability I S S
Design for Six Sigma (DFSS) I S O
Design for X (DFX) I S O
Design of experiments
Three factor, three level experiment I O O
Randomized block plans I S O
Latin square designs I O O
Graeco-Latin designs I S O
Full factorial designs I O O
Plackett-Burman designs I S O
Taguchi designs I O O
Taguchi’s robust concepts I S O
Mixture designs I S O
Central composite designs I S S
EVOP evolutionary operations I I S
DMADV (Define, Measure, Analyze, Design, Verify) S O O
DMAIC (Define, Measure, Analyze, Improve, Control) O O O
Effort/impact analysis I O O
Equipment certification S S S
Error proofing O O O
Exponential distribution I O O
External and internal customers O O O
F-distribution I S S
Facilitation of teams I O O
Factorial experiments I S O
Failure mode and effects analysis O O O
Fast-action solution team (FAST) O O S
First-time yield (FTY) or rolled-through yield (RTY) O O O
Five whys (5Ws) O O O
Flowcharts O O O
Focus groups S O O
Force field analysis O O O
Frequency distribution O O O
Future state mapping O O O
Gantt charts O O O
Gaussian curves I S S
General surveys O O O
Histograms O O O
History of quality S S S
Hypergeometric distribution I S O
Hypothesis testing
Fundamental concepts S O O
Point and interval estimation I S O
Tests for means, variances, and proportions I O O
Paired comparison tests I O O
Analysis of variance O O O
Contingency tables S O O
Nonparametric tests S O O
Interrelationship diagraphs (IDs) S O O
Interviewing techniques O O O
IT applications S O O
Just-in-time I S S
Kaizen and you A A A
Kaizen and process troubleshooting S O O
Kaizen and teams S O O
Kaikaku (transformation of mind) I S O
Kanban S S S
Kano model S O O
Kendall coefficient of concordance I I S
Knowledge management I S O
KPIs O O O
Kruskal-Wallis one-way analysis I S S
Lean thinking S O O
Levene test I S S
Lognormal distribution I S S
Loss function S O O
Management theory history I S O
Mann-Whitney U-test I S S
Market segmentation S S O
Matrix diagrams O O O
Measure of dispersion O O O
Measurement error O O O
Measurement systems S O O
analysis (MSA)
Measurement tools O O O
Method of least squares O O O
Mistake proofing (poka-yoke) S S S
Mood’s median test I S S
Motivating the workforce S O O
Multivari analysis S O O
Multiple linear regression S O O
Negotiation techniques O O O
Nominal group technique O O O
Normal distribution O O O
Normal probability plots S O O
Null hypothesis S O O
Opportunity cycle (protection, analysis, correction, measurement, prevent) S S S
Project management A A A
Organizational change management O O O
Organizational culture diagnosis S O O
Overall equipment effectiveness (OEE) S S S
Pareto diagrams A A A
Pattern and trend analysis I S S
Plan-Do-Check-Act (PDCA) S S S
Plan, Understand, Streamline, Implement Continuous Improvement (PUSIC) S O O
Point of use storage (POUS) O O O
Poisson distribution S O O
Poka-yoke (mistake proofing) S S S
Poor-quality cost S S O
Portfolio project management I S O
Prioritization matrices O O O
Probability concepts O O O
Probability density function I S O
Probability plots O O O
Process capability studies O O O
Process decision program charts (PDPC) S O O
Process elements O O O
Process fail points matrix S S S
Process mapping O O O
Process performance matrix S O O
Process redesign S O O
Program evaluation and review technique (PERT) I S S
Poisson series I S O
Project decision analysis I S O
Project financial benefits analysis A A A
Project selection matrix I S A
Pugh concept selection I I I
Pull systems S O O
Quality @ source O O O
QFD (quality function deployment) S O O
Qualitative factor O O O
Quantitative factor O O O
Re-engineering I S O
Regression analysis S O O
Reliability analysis I S O
Response surface methodology (RSM) I S S
Rewards and recognition S O O
Risk analysis A A A
Risk assessment A A A
Robust design approach S O O
Root cause analysis A A A
Sampling O O O
SCAMPER S S S
Scatter diagrams O O O
Seven basic tools O O O
Sigma O O O
Sigma conversion table O O O
Signal-to-noise ratio I S O
Simple language S O O
Simple linear regression S O O
Simplification approaches O O O
Simulation modeling I S O
Single-minute exchange of die (SMED) I S O
Six Sigma metrics I S O
Spearman rank correlation coefficient I S O
Stakeholders O O O
Standard work A S S
Statistical process control O O O
Statistical tolerance S S O
Stem and leaf plots I S O
Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis S O O
Structural roadblocks S O O
Student’s t-distribution I S O
Supplier controls S O O
Supplier, inputs, process, outputs, customers (SIPOC) diagrams O O O
Systematic design S S O
Takt time S S O
Team building O O O
Team charter A A A
Team management A A A
Theory of constraints S S O
Throughput yield (TPY) I S S
Tollgates O A A
Total Productive Maintenance (TPM) S S O
Tree diagrams O O O
TRIZ I I I
Types of data O O O
Types of teams I S O
Value/No-value-added activities S O O
Value stream analysis (mapping) S O O
Value stream management S O A
Variance (o2, s2) I O O
Variation analysis
Rational subgroups S O O
Sources of variability S O O
Randomness testing S O O
Precontrol techniques I S O
Exponentially weighted moving average (EWMA) I S S
Moving average S O O
Visual factory/visual office S O O
Voice of the customer (VOC) A A A
Voice of the supplier (VOS) O O O
Waste identification A A A
Waste elimination A A A
Weibull distribution I O O
Wilcoxon-Mann-Whitney rank sum test I S S
Work breakdown structure O O O
Work standard I S O
Z-value I S O
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