Lean Six Sigma Black Belt Topics 

Lesson Title 
Topic 
Overview 
A toplevel overview of the topics covered in this course 
What is Six Sigma? 
A complete toplevel overview 
Lean Overview 1 
Waste and Value 
Lean Overview 2 
Value Streams, Flow and Pull 
Lean Overview 3 
Perfection 
Recognizing an Opportunity 
Linking your Black Belt activities to the organization’s vision and goals 
Choosing the ProjectPareto Analysis 
How to pick a winning project using Pareto Analysis 
Assessing Lean Six Sigma Project Candidates 
How to carefully assess Lean Six Sigma project candidates to assure success 
Develop the Project Plan 1 
Team selection and dynamics; brainstorming; consensus decision making; nominal group technique 
Develop the Project Plan 2 
Stakeholder analysis, communication and planning, cross functional collaboration, and Force Field Analysis 
Develop the Project Plan 3 
Obtain a charter for your project 
Develop the Project Plan 4 
Work breakdown structures, DMAIC tasks, network diagrams 
Develop the Project Plan 5 
Project schedule management; project budget management 
Develop the Project Plan 6 
Obstacle avoidance tactics and management support strategies 
High Level Maps 1 
LMaps, linking project charter Ys to LMap processes 
High Level Maps 2 
Mapping the process from supplier to customer (SIPOC) 
High Level Maps 3 
Product family matrix 
Voice of the Customer (VOC) 1 
Kano Model, getting the voice of the customer using the critical incident technique 
VOC 2Survey Development 
Using the output of the CIT process to develop and validate surveys 
VOC 3Listening to Customers 
Focus groups and other customer listening posts 
VOC 4Analytic Hierarchical Process (AHP) 
How to determine customer importance weights 
VOC 5CTQ Specification 
Link the voice of the customer to the CTQs that drive it 
Principles of Variation 1 
How will I measure success? Are my measurements trustworthy? Scales of measurement, data types, measurement error principles. 
Principles of Variation 2 
Enumerative and analytic studies; statistical process control principles; operational definitions 
Establish the Process Baseline 1 
Descriptive statistics for measuring distribution location, spread, and shape 
Establish the Process Baseline 2 
Control charts for location or central tendency: averages, ranges, standard deviations, individual observations, and moving ranges. 
Establish the Process Baseline 3 
Control charts for discrete data (attributes control charts.) p, np, c and u charts 
Establish the Process Baseline 4 
Control chart selection and interpretation 
Establish the Process Baseline 5 
Discrete distribution:Binomial, Poisson, Hypergeometric 
Establish the Process Baseline 6 
Continuous probability distributions for Lean Six Sigma: normal, exponential, chisquare, Student’s t, F 
Establish the Process Baseline 7 
Process capability analysis 
Establish the Process Baseline 8 
Rolled throughput yield, normalized yield, process sigma level 
Establish the Process Baseline 9 
Create detailed pictures of the asis process 
Establish the Process Baseline 10 
Spaghetti charts 
Establish the Process Baseline 11 
Current state value stream map 
Test Theories with Data 1 
Statistical inference 
Stratify Data 1 
Data collection and sampling for stratification 
Stratify Data 2 
Data stratification tools: tree diagrams, Pareto analysis, matrix diagrams, check sheets, defect location maps 
Stratify Data 3 
Distributionsgraphical data summaries. Histograms and frequency plots. 
Stratify Data 4 
Exploratory Data Analysis (EDA). Box plots, stemandleaf plots. 
Set Goals for the Outputs 1 
Benchmarking as an aid in goal setting 
Set Goals for the Outputs 2 
Project FMEA 
Focus the Problem StatementOpportunity Maps 
Use activity maps to identify value added activities 
Design a Lean Value Stream 
Lean principles; future state value stream map 
Develop Theories 1 
Brainstorming, causeandeffect diagrams (Ishikawa diagrams, fishbone diagrams) 
Develop Theories 2 
Root cause analysis, event and causal factor tree, fault tree analysis. 
Test Theories with Data 2 
Testing common assumptions: data type, independence, normality 
Test Theories with Data 3 
Experimentation concepts and sample size 
Test Theories with Data 4 
Testing one way classifications: ttests, ANOM, 1Way ANOVA, KruskalWallis 
Test Theories with Data 5 
Two way classification analysis: ANOVA, ANOM 
Test Theories with Data 6 
Analysis of twoway tables of counts using chisquare 
Test Theories with Data 7 
Nonparametric testing with Minitab 
Model CauseandEffect 1 
Correlation analysis, scatter plots 
Model CauseandEffect 2 
Regression analysis, linearizing transformations 
Model CauseandEffect 3 
Analysis of residuals from regression analysis 
Model CauseandEffect 4 
Designing and analyzing screening experiments using Minitab 
Model CauseandEffect 5 
Factorial and fractional factorial designed experiments using Minitab 
Creating Flow 
Select the subproject, identify highimpact variables, design pull systems, design continuous flow work cells, choosing and maintaining equipment, 5S, etc. 
Analysis of Costs and Benefits 
Financial analysis including present value, future value, net present value, internal rate of return 
Measurement Systems Analysis 1 
Analysis of continuous data measurement systems (taught here, but used earlier in actual projects) 
Measurement Systems Analysis 2 
Analysis of attributes measurement systems 
Determine Improvement Strategy 01 
Improvement project planning, pilot study, simulation 
Determine Improvement Strategy 02 
Risk assessment and mitigation using prioritization matrices, FMEA and process decision program charts (PDPC) 
Implement 1 
Institutionalize your changes 
Implement 2 
Process control planning, process control principles, choosing the process elements to monitor, approaches to process control, and next steps. 
Implement 3 
Process deployment maps 
Implement 4 
Dashboards for process control and improvement 
Implement 5 
Training needs analysis, continuous improvement with KAIZEN, Kaizen events, extend flow to suppliers and customers, project closure 