Lean Six Sigma Black Belt Topics

Lesson Title



A top-level overview of the topics covered in this course

What is Six Sigma?

A complete top-level overview

Lean Overview 1

Waste and Value

Lean Overview 2

Value Streams, Flow and Pull

Lean Overview 3


Recognizing an Opportunity

Linking your Black Belt activities to the organization’s vision and goals

Choosing the Project-Pareto 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

L-Maps, linking project charter Ys to L-Map 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 2-Survey Development

Using the output of the CIT process to develop and validate surveys

VOC 3-Listening to Customers

Focus groups and other customer listening posts

VOC 4-Analytic Hierarchical Process (AHP)

How to determine customer importance weights

VOC 5-CTQ 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, chi-square, 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 as-is 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

Distributions-graphical data summaries. Histograms and frequency plots.

Stratify Data 4

Exploratory Data Analysis (EDA). Box plots, stem-and-leaf 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 Statement-Opportunity 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, cause-and-effect 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: t-tests, ANOM, 1-Way ANOVA, Kruskal-Wallis

Test Theories with Data 5

Two way classification analysis: ANOVA, ANOM

Test Theories with Data 6

Analysis of two-way tables of counts using chi-square

Test Theories with Data 7

Non-parametric testing with Minitab

Model Cause-and-Effect 1

Correlation analysis, scatter plots

Model Cause-and-Effect 2

Regression analysis, linearizing transformations

Model Cause-and-Effect 3

Analysis of residuals from regression analysis

Model Cause-and-Effect 4

Designing and analyzing screening experiments using Minitab

Model Cause-and-Effect 5

Factorial and fractional factorial designed experiments using Minitab

Creating Flow

Select the subproject, identify high-impact 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