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Six Sigma Black Belt Curriculum

Six Sigma Black Belt Curriculum

Module 1: Define

Introduction to Six Sigma

  • History of Six Sigma

  • Need for Six Sigma

  • Six Sigma metrics

  • DMAIC (Define, Measure, Analyze, Improve, Control) methodology overview

  • Examples of Six Sigma results

Voice of the customer (VOC)

CTx (quality, time, cost)

Converting VOC to CTQs (critical to quality)

SIPOC (supplier, input, process, output, customer)

Pareto analysis

Project charter

  •  Business opportunity

  •   Problem statement  

  •   Objective primary and secondary metrics

  •    Scope

  •    Cost of poor quality (COPQ)

  •     Project teams

Stakeholder analysis

Module 2 : Measure

Process mapping

Fishbone diagram

Graphical tools

  • Histogram

  • Dot plot

  • Boxplot

  • Scatterplot

  • Time series plot

  • Pareto chart

Basic statistics and probability

  •  Types of data

  • Accuracy versus precision

  • Mean, median, mode

  • Range, interquartile range, variance, standard deviation

  • Sample versus population

  • Percentiles

  • Central limit theorem

  • Confidence intervals

Process distributions

  • Normal distribution

  • Exponential, Weibull, lognormal

  • Binomial, Poisson

Lean concepts

  •  Value stream, flow

  • Batch versus single-piece flow

  • Seven forms of waste

  • Push versus pull systems

  • Kanbans, work cells

  • Supply chain, just-in-time

  • 5S (sort, straighten, shine, standardize, sustain) and visual management

  • Standard work

  • OEE (overall equipment effectiveness)

Sampling and data collection

  • Sampling bias

  • Sampling techniques:  random, stratified random, systematic, rational subgrouping

  • Power and sample size calculations

Process capability

  • Process stability

  • Normal capability analysis (Cp, Cpk, CPM, Pp, Ppk)

  • Non-normal capability analysis

  • Binomial and Poisson capability analysis

  • Rolled throughput yield (RTY), defect per unit (DPU), defects per million opportunities (DPMO), Sigma level (including shift)

Measurement system analysis

  • Variable gage R&R

  • Destructive testing

  • Crossed versus nested designs

  • Attribute Gage R&R

Module 3 : Analyze

Failure mode and effects analysis (FMEA)

Multi-vari analysis

Inferential probability distributions

  • Normal

  • Chi-square

  • True, False

  • Binomial, Poisson

Hypothesis testing

  • Anderson-Darling normality test

  • One-sample t-test

  • Two-sample t-test

  • Paired t-test

  • One-way analysis of variance (ANOVA)

  • One-sample test for variation

  • Two-sample test for variation

  • Test for equal variance

  • One-sample sign

  • Mood’s median test

  • One-proportion test

  • Two-proportion test

  • Chi-squared contingency table

  • One-sample Poisson rate

  • Two-sample Poisson rate

General ANOVA

Correlation and regression

Multiple regression

Binary logistic regression

Design of experiments (DOE) strategies

2k full factorial DOE

DOE center points, blocking, covariates

2k fractional factorial DOE

General full factorial DOE

Central composite design

Module 4 : improve

Innovative solutions (brainstorming, etc.)

Selecting a solution (Pugh matrix)

DOE multiple response optimization

Response surface methodology

Evolutionary operation (EVOP)

Lean tools

  • Lean measures of time:  lead time, takt time, completion time, cycle time 
  • Value stream mapping

  • Time value mapping

  • Theory of constraints

  • Load charts/line balancing

  • Spaghetti chart

Queuing theory

Improve techniques

  • Self-inspection

  • Training

  • Checklist

  • Process simplification

  • Mistake proofing

Implementation and verification (piloting, etc.)

Module 5 : Control

Statistical process control

  • I-MR charts
  • Xbar-R charts

  • Xbar-S charts

  • P-charts

  • C-charts

  • U-charts

Control plans

  •  What, who, where, how often, how much

  • Decision criteria

 Action plan

  • Management engagement and handoff

  • Project closure 

Here are some tips which  might help you before taking up the exam :

  • Initially, be familiar with all the definitions and topics of each and every chapter. The below table shows you the percentage of questions from each section
 Section Title  % of Exam
 IX  Analyze     15%
 V  Define -Tools  15%
 VI  Measure - Data 12%
 III  Lean - DFSS 10%
 IV  Define - Teams 10%
 VII  Measure - Portability 10%
 VIII  Measure - Capability 8%
 XI  Control Concepts 8%
 X  Improvement 7%
 II  Six Sigma Goals 5%


  • Maintain a notepad with you where you can mention your keywords and topics that you can quickly revise before taking up the exam

  • Do answer the sample questions at the end of every chapter. After answering all the questions go through the questions which are incorrect, read the explanation and make a note of it which would be helpful

  • Review each section as many times as possible

  • Start with easy questions. Do not stay on the problem that you are stuck on. If you skip any question make a star mark on it so you can quickly find out.

  • Arrive early to the exam hall