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Lean Six Sigma Black Belt

Learn the Lean Six Sigma Black Belt methodologies and enhance your career. Become a leader in process optimization. Enroll now! Read more.

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Course Skill Level
Intermediate
Time Estimate
38h 59m

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About This Course

Who this course is for:

  • This course is ideal for professionals across various industries, including manufacturing, healthcare, finance, and services, who aim to enhance their careers and drive organizational excellence using Lean Six Sigma methodologies. Whether you’re a quality manager, process improvement specialist, project manager, or aspiring leader, this course will empower you to lead transformative change initiatives and deliver measurable, sustainable results.

What you’ll learn: 

  • Develop a thorough understanding of Lean Six Sigma principles and advanced techniques.
  • Master the DMAIC methodology and its application to complex process improvement projects.
  • Develop advanced skills in data collection, statistical analysis, and process capability assessment.
  • Learn Lean principles and tools to effectively identify and eliminate waste.
  • Explore proven strategies to sustain improvements through control plans and Lean controls.
  • NOTE: Expect to learn from multiple speakers with diverse backgrounds and experience, ensuring a well-rounded educational experience.

Requirements: 

  • A foundational understanding of basic math concepts.
  • Familiarity with general business and operational concepts.

The Lean Six Sigma Black Belt course is designed by experts to provide you with the advanced skills needed to excel in Lean Six Sigma. Throughout this comprehensive program, you will dive deep into key topics in process improvement and quality management, with a focus on practical, real-world applications. Our expert instructors will guide you through complex concepts and methodologies, ensuring you gain both the knowledge and confidence to implement change.

This course covers essential topics such as Lean Six Sigma principles, the DMAIC methodology, Lean Enterprise, and advanced statistical analysis. You will participate in practical exercises and case studies that reinforce your understanding and build your problem-solving skills. Additionally, the course offers effective strategies for implementing Lean Six Sigma tools, such as design of experiments, regression analysis, and control methods.

Why Choose This Course?
Our Lean Six Sigma Black Belt course is designed with expertise to help you not only understand theory but also apply these principles effectively in the real world. As you progress through the course, you’ll learn from industry experts with years of experience and obtain practical insights that you can apply right away in your professional role. This practical, hands-on learning approach ensures that you’re not just prepared for certification, but ready to lead impactful change and contribute meaningfully to your organization’s success.

Curious about how to make a lasting impact on the world? My courses can equip you with the skills you need.

Our Promise to You

Upon completing this course, you will have the advanced knowledge and practical skills necessary to lead high-impact process improvement initiatives and drive measurable success in your organization.

10 Day Money Back Guarantee. If you are unsatisfied for any reason, simply contact us and we’ll give you a full refund. No questions asked.

Get started today!

Course Curriculum

Section 1 - Course Overview
Course Overview-LSSBB 00:00:00
Section 2 - Lean Six Sigma Introduction
Lean Six Sigma And Process Issues 00:00:00
Section 3 - Six Sigma Overview
Foundation – Introduction 00:00:00
DPMO And Z Score 00:00:00
Example 1 DPMO And Z Score 00:00:00
Example 2 DPMO And Z Score 00:00:00
1.5 Sigma Shift 00:00:00
History Of Six Sigma 00:00:00
History Of Continuous Improvement 00:00:00
Six Sigma Organization 00:00:00
Section 4 - DMAIC Methodology Page
DMAIC Methodology-Six Sigma Methodologies 00:00:00
DMAIC Phases 00:00:00
Example DMAIC Phases 00:00:00
DMAIC Methodology 00:00:00
DMAIC Approach 00:00:00
What A Function Is: Y = f(X) 00:00:00
Six Sigma Success Or Failure 00:00:00
Section 5 - Lean Enterprise
Lean Introduction And History 00:00:00
Lean Approach-01 00:00:00
Lean Approach-02 00:00:00
Lean Approach-03 00:00:00
Example-Jidoka And Quick Changeover 00:00:00
Example-Kanban And Pull Systems And One-Piece Flow 00:00:00
Takt Time And Cycle Time 00:00:00
Value-Added, Non-Value-Added And Waste 00:00:00
Lean Thinking – Add Value 00:00:00
Waste (Muda) 00:00:00
Types Of Waste And Common Causes 00:00:00
Lean Methodology And Tools 00:00:00
Value Stream Mapping (VSM) 00:00:00
5S Or 6S 00:00:00
Kaizen And Types 00:00:00
End Of Module—Summary 00:00:00
Section 6 - Define Phase Overview
Define Phase 00:00:00
Overview 00:00:00
Define Phase – Lean Six Sigma Black Belt 00:00:00
Section 7 - Voice Of Customer (VOC)
VOC Capturing Methods 00:00:00
Kano Analysis 00:00:00
Business Processes 00:00:00
Business Performance Measure (BPM) 00:00:00
Section 8 - Critical To Quality (CTQ)
CTQ 00:00:00
Critical To Quality (CTQ): Flow-Down – CTQ Tree 00:00:00
Translation Of VOC To CTQ 00:00:00
COPQ And 1-10-100 Rule 00:00:00
COPQ 00:00:00
Pareto Chart 00:00:00
Project Primary And Secondary Metrics 00:00:00
Throughput Yield (TPY) 00:00:00
Rolled Throughput Yield 00:00:00
Section 9 - SIPOC Page
SIPOC 00:00:00
Section 10 - Stakeholder Analysis
Stakeholder Analysis 00:00:00
Stakeholder Management 00:00:00
Section 11 - Project Charter
Project Selection 00:00:00
Project Charter 00:00:00
Financial Benefits 00:00:00
Payback Period 00:00:00
Business Case 00:00:00
Project Scope 00:00:00
Project Charter – Summary 00:00:00
Differences Between ARMI And RASIC Tools 00:00:00
Section 12 - Measure Phase Overview
Measure Phase Introduction 00:00:00
Measure Overview 00:00:00
Measure Phase – Lean Six Sigma Black Belt 00:00:00
Section 13 - As-Is Process Review (Process Definition)
Process Map Overview-1 00:00:00
Process Map Overview-2 00:00:00
Type Of Process Mapping 00:00:00
Detailed Process Mapping 00:00:00
Value Stream Mapping (VSM) 00:00:00
VSM – Creation 00:00:00
VSM Common Metrics 00:00:00
VSM – Calculation (Little’s Law) 00:00:00
Value Add Flow Analysis 1 00:00:00
Value Add Flow Analysis 2 00:00:00
Value Add Flow Analysis Exercise 00:00:00
Spaghetti Diagram 00:00:00
X Y Matrix 00:00:00
X Y Matrix Example 00:00:00
5 Whys 00:00:00
5 Whys Example 00:00:00
Fishbone Diagram – 1 00:00:00
Fishbone Diagram – 2 00:00:00
Fishbone Diagram Example 00:00:00
Failure Mode And Effects Analysis (FMEA) 00:00:00
FMEA Other Details 00:00:00
FMEA Template 1 00:00:00
FMEA Template 2 00:00:00
FMEA Rating 00:00:00
FMEA Example 00:00:00
Section 14 - Data Collection And Analysis (Basic Statistics)
Data Collection – Introduction 00:00:00
Data Types 00:00:00
Qualitative Data – Additional Detail 00:00:00
Ranked Data 00:00:00
Operational Definition 00:00:00
Data Stratification 00:00:00
Data Collection Planning 00:00:00
Data Sampling 00:00:00
Data Analysis-Graphical-1 00:00:00
Data Analysis-Graphical-2 00:00:00
Box Plot – Additional Detail 00:00:00
Statistical Analysis – Software 00:00:00
Minitab Introduction 00:00:00
Pulse Example 00:00:00
Pulse Example – Excel 00:00:00
Pulse Example – Histogram 00:00:00
Pulse Example – Box Plot 00:00:00
Pulse Example – Dot Plot 00:00:00
Pulse Example – Stem And Leaf Plot 00:00:00
Pulse Example – Time Series 00:00:00
Pulse Example – Scatter Plot 00:00:00
Data Analysis- Descriptive Statistics 00:00:00
Center Tendency 00:00:00
Center Tendency – Distribution And Data Type 00:00:00
Variability And Dispersion 00:00:00
Symbols For Data 00:00:00
Section 15 - Data Accuracy And Precision (Measurement System Analysis - MSA)
Measurement System Analysis (MSA) – Overview 00:00:00
Measurement System Analysis – Introduction 00:00:00
MSA – Elements 00:00:00
MSA – Elements Exercise 00:00:00
Measurement Error 00:00:00
Measurement Error – Types 00:00:00
Appropriate Measures 00:00:00
Measurement System Analysis (MSA) 00:00:00
MSA – Formula 00:00:00
Percent Tolerance GRR 00:00:00
MSA – Procedure-1 00:00:00
MSA – Procedure-2 00:00:00
MSA – Procedure-3 00:00:00
Example Variable Gage R-R 00:00:00
Example Variable Gage R-R – Excel 00:00:00
Minitab – Variable GRR Methods 00:00:00
Minitab – VGRR 1- Example 00:00:00
Minitab – VGRR 2- Example 00:00:00
Attribute Agreement Analysis 00:00:00
Attribute MSA AAA–Introduction 00:00:00
Attribute MSA – Kappa Statistic 00:00:00
Attribute MSA AAA–Purpose 00:00:00
AAA 1 – Example 00:00:00
AAA 2 – Example 00:00:00
AAA 3 – Example 00:00:00
MSA – Improvement Actions And Summary 00:00:00
Section 16 - Process Capability, Distribution Types, And Stability
Process Capability – Overview 00:00:00
Process Capability – Introduction-I 00:00:00
Process Capability – Introduction-II 00:00:00
Process Capability Analysis 00:00:00
Process Capability – Metrics Cp Cpk Or Pp Ppk 00:00:00
Process Capability – Z Score 00:00:00
IASSC Reference Document – Introduction 00:00:00
Process Capability – Z-Score – Example 00:00:00
Process Capability – Sigma Levels 00:00:00
Process Capability – 1.5 Sigma Shift 00:00:00
Types Of Distributions 00:00:00
Normal Distribution 00:00:00
Example – Normality Test 00:00:00
Example – Process Capability For Normal Data 00:00:00
Non-Normal Data And Transformation 00:00:00
Example – Non-Normal Distribution – Identification 00:00:00
Example – Process Capability For Non-Normal Data 00:00:00
Process Capability – Attribute Data 00:00:00
Binomial And Poisson Process Capability 00:00:00
Binomial Process Capability – Example 00:00:00
Poisson Process Capability – Example 00:00:00
Process Stability– Overview 00:00:00
Control Charts 00:00:00
Process Stability – Example 00:00:00
Process Capability And Stability 00:00:00
End Of Measure Phase Module – Summary 00:00:00
Section 17 - Analyze Phase - Overview
Analyze – Introduction 00:00:00
Analyze Phase – Overview-I 00:00:00
Analyze Phase – Overview-II 00:00:00
Analyze Phase -Lean Six Sigma Black Belt 00:00:00
Section 18 - Patterns Of Variation
Sources-Causes Of Variation 00:00:00
Multi-Vari Chart Analysis 00:00:00
Example: Multi-Vari Chart-I 00:00:00
Example: Multi-Vari Chart-II 00:00:00
Classes Of Distributions 00:00:00
Causes Of Non-Normal Distributions 00:00:00
Non-Normal Distributions: Skewness 00:00:00
Non-Normal Distributions: Kurtosis 00:00:00
Non-Normal Distributions: Multiple Modes And Granularity 00:00:00
Non-Normal Data 00:00:00
Section 19 - Inferential Statistics
Inferential Statistics-Introduction 00:00:00
Confidence Interval 00:00:00
Sampling 00:00:00
Sampling Methods 00:00:00
Example-Sampling 00:00:00
Sample Size 00:00:00
Sampling Bias 00:00:00
Central Limit Theorem (CLT) 00:00:00
Standard Error (SE) 00:00:00
Confidence Interval Of Mean 00:00:00
95 Percent Confidence Interval Of Mean 00:00:00
Confidence Interval-Example 1 00:00:00
Confidence Interval-Example 2 00:00:00
Confidence Interval-Example 2-Excel 00:00:00
Confidence Interval-Example 2-Minitab 00:00:00
Section 20 - Hypothesis Testing
Hypothesis Testing 00:00:00
Six Sigma Project And Hypothesis Testing 00:00:00
Hypothesis And Hypothesis Testing 00:00:00
Significant Differences 00:00:00
Hypothesis Test Options – Normal Data 00:00:00
Hypothesis Test Options – Non-Normal Data 00:00:00
Hypothesis Test Roadmap 00:00:00
Hypothesis Statements Examples 00:00:00
Hypothesis Testing Procedure 00:00:00
P-Value 00:00:00
Risk – Types 00:00:00
Risk – Alpha And Beta 00:00:00
P-Value And Alpha Risk 00:00:00
Statistical Power 00:00:00
Hypothesis Test – In A Nutshell 00:00:00
Section 21 - Hypothesis Testing With Normal Data
Hypothesis Testing With Normal Data 00:00:00
T-Test_Introduction 00:00:00
Example_1-Sample T-Test-V1 00:00:00
Example_1-Sample T-Test-V2 00:00:00
Example_2-Sample T-Test 00:00:00
Example_Paired T-Test-V1 00:00:00
Example_Paired T-Test-V2 00:00:00
Variance Test_Introduction 00:00:00
Example_1- Variance Test-V1 00:00:00
Example_1- Variance Test-V2 00:00:00
Example_2- Variance Test 00:00:00
ANOVA-Introduction 00:00:00
ANOVA-Purpose 00:00:00
ANOVA Test Methods 00:00:00
One-Way ANOVA Table 00:00:00
Example_One-Way ANOVA 00:00:00
Example_One-Way ANOVA_Minitab 00:00:00
Example_Balanced ANOVA-Minitab 00:00:00
Example_Balanced ANOVA-V1 00:00:00
Example_Balanced ANOVA-V2 00:00:00
Example_Balanced ANOVA-V3 00:00:00
Section 22 - Hypothesis Testing With Non-Normal Data
Hypothesis Testing With Non-Normal Data 00:00:00
Nonparametric Tests 00:00:00
One-Sample Sign Test 00:00:00
Example_One-Sample Wilcoxon Test 00:00:00
One-Sample Wilcoxon Signed Rank Test 00:00:00
Example_Test Statistics And Estimated Median 00:00:00
Example_One-Sample Wilcoxon Test-Minitab 00:00:00
Mann-Whitney Test 00:00:00
Example_Mann-Whitney Test 00:00:00
Kruskal-Wallis Test 00:00:00
Example_Kruskal-Wallis Test 00:00:00
Mood’s Median Test 00:00:00
Example_Mood’s Median Test 00:00:00
Friedman Test 00:00:00
Example_Friedman Test 00:00:00
1-Proportion Test 00:00:00
Example: 1-Proportion Test 00:00:00
2-Proportion Test 00:00:00
Example: 2-Proportion Test 00:00:00
Chi-Square Test And Contingency Table 00:00:00
Example: Chi-Square Test-V1 00:00:00
Example: Chi-Square Test-V2 00:00:00
End Of Analyze Phase Module-Summary 00:00:00
Section 23 - Improve Overview
Improve – Introduction 00:00:00
Improve Phase – Overview 00:00:00
Improve Phase – DMAIC Roadmap 00:00:00
Improve Phase – Lean Six Sigma Black Belt 00:00:00
Section 24 - Potential Solutions Generation
Potential Solutions 00:00:00
Solution Or Improvement Hierarchy 00:00:00
Industrial Revolution 4.0 00:00:00
TRIZ-1 00:00:00
TRIZ-2 00:00:00
TRIZ 39 Matrix And 40 Principles 00:00:00
TRIZ Separation Principles 00:00:00
Section 25 - Lean Solutions And Tools
Lean Solutions Most Common Tools 00:00:00
5S Approach-1 00:00:00
5S Approach-2 00:00:00
Visual Factory Management 00:00:00
Kanban-1 00:00:00
Kanban-2 00:00:00
Kanban-3 00:00:00
Jidoka And Andon 00:00:00
Total Productive Maintenance 00:00:00
Quick Changeover 00:00:00
Section 26 - Mistake-Proofing
Mistake-Proofing 00:00:00
Examples Mistake-Proofing 00:00:00
Human Errors 00:00:00
Mistake-Proofing Methods 00:00:00
Section 27 - Select The Best Solution
Select The Best Solution 00:00:00
Assess The Risks 00:00:00
Section 28 - Pilot Implementation
Pilot And Future Map 00:00:00
Standardized Work 00:00:00
Solution Implementation 00:00:00
Section 29 - Simple Linear Regression
Regression Introduction 00:00:00
Correlation 00:00:00
Regression Types 00:00:00
Simple Linear Regression 00:00:00
R-Squared 00:00:00
Example-Simple Linear Regression 00:00:00
Example-SLR—Analysis 00:00:00
Example-SLR—Analysis CI And PI 00:00:00
Residual 00:00:00
Residual—Assumptions 00:00:00
Example-SLR—Residual Plot 00:00:00
Example-SLR-Minitab 00:00:00
Section 30 - Multiple Regression Analysis (MRA)
MRA-Introduction 00:00:00
Nonlinear Data 00:00:00
Example-Polynomial Regression 00:00:00
Nonlinear Data-Transformation 00:00:00
Example Transformation-Minitab 00:00:00
Multiple Linear Regression 00:00:00
MLR-Simple Model 00:00:00
MLR-Complex Model 00:00:00
Nonlinear Regression 00:00:00
Multiple Linear Regression-Steps 00:00:00
Example_MLR—Matrix Plot 00:00:00
Example_MLR—Best Subsets 00:00:00
Example_MLR—ANOVA 00:00:00
Example_MLR—ANOVA (Repeat And Final) 00:00:00
Example_MLR—Residual Analysis 00:00:00
Section 31 - Designed Experiments Or Design Of Experiments (DOE)
DOE Introduction And Objectives 00:00:00
DOE Factors And Levels 00:00:00
DOE Treatments And Combinations 00:00:00
DOE Response Main Effect Interaction 00:00:00
Example-Cooking DOE-V1 00:00:00
Example-Cooking DOE-V2 00:00:00
DOE Multicollinearity 00:00:00
DOE Confounding Variables 00:00:00
DOE Experimental Error 00:00:00
DOE Randomization 00:00:00
DOE Replication 00:00:00
DOE Blocking 00:00:00
DOE Balanced And Orthogonal Designs 00:00:00
DOE Center Points 00:00:00
DOE Design Methods-V1 00:00:00
DOE Design Methods-V2 00:00:00
DOE Design Methods-V3 00:00:00
DOE Design Methods-V4 00:00:00
DOE Create Factorial Design-Example 00:00:00
Section 32 - Full Factorial Experiments
2k Full Factorial Designs 00:00:00
Mathematical Models 00:00:00
Quadratic Mathematical Models 00:00:00
Fit And Diagnose-Overview 00:00:00
Example-2k Full Factorial Design 00:00:00
Example-Create Factorial Design 00:00:00
Example-Analyze Factorial Design-V1 00:00:00
Example-Analyze Factorial Design-V2 00:00:00
Example-Analyze Factorial Design-V3 00:00:00
Example-Analyze Factorial Design-V4 00:00:00
Example-Factorial Plots 00:00:00
Example-Cube Plot 00:00:00
Example-Surface Plot 00:00:00
Example-Contour Plot 00:00:00
Example-Contour Plot Of Cost 00:00:00
Example-Response Optimizer 00:00:00
Fractional Factorial Designs 00:00:00
Confounding Effect 00:00:00
Experimental Resolutions 00:00:00
IP EoM Summary 00:00:00
Section 33 - Control Phase - Overview
Control Phase: Introduction 00:00:00
Control Phase – V1 00:00:00
Control Phase – V2 00:00:00
Control Phase – Lean Six Sigma Black Belt 00:00:00
Section 34 - Lean Controls
Lean Controls 00:00:00
Lean Controls: 5S, Kanban, And Poka-Yoke 00:00:00
Lean Controls: Kaizen 00:00:00
Section 35 - Statistical Process Control
Statistical Process Control 00:00:00
Control Charts 00:00:00
Control Charts: Anatomy 00:00:00
Control Charts: Variation 00:00:00
Control Charts: Decision Rules-V1 00:00:00
Control Charts: Decision Rules-V2 00:00:00
Control Charts: Decision Rules-V3 00:00:00
Control Charts: Types For Continuous Data -V1 00:00:00
Control Charts: Types For Continuous Data -V2 00:00:00
Control Charts: Types For Attribute Data 00:00:00
Control Charts And Decision Rules 00:00:00
Control Charts: I-MR Chart Formulas 00:00:00
Control Charts: X-Bar R Chart Formulas 00:00:00
Control Charts: X-Bar S Chart Formulas 00:00:00
Control Charts: Attributes Chart Formulas-V1 00:00:00
Control Charts: Attributes Chart Formulas-V2 00:00:00
Control Charts: Data Collection 00:00:00
Control Charts Average Run Length 00:00:00
Control Charts: Four States 00:00:00
Control Charts Control Methods 00:00:00
Example: I-MR Chart 00:00:00
Example: X-Bar R Chart 00:00:00
Example: P Chart 00:00:00
Example U Chart 00:00:00
Time-Weighted Control Charts 00:00:00
EWMA Charts 00:00:00
EWMA Charts Formula V1 00:00:00
EWMA Charts Formula V2 00:00:00
EWMA Charts Example 00:00:00
CUSUM Charts 00:00:00
CUSUM Charts Types 00:00:00
CUSUM Charts Example 00:00:00
Section 36 - Six Sigma Control Plan
Control Plans 00:00:00
Implementation Plans 00:00:00
Control Plans Five Elements 00:00:00
Control Plan Preparation 00:00:00
Project Closure 00:00:00
CP EoM Summary 00:00:00

About This Course

Who this course is for:

  • This course is ideal for professionals across various industries, including manufacturing, healthcare, finance, and services, who aim to enhance their careers and drive organizational excellence using Lean Six Sigma methodologies. Whether you’re a quality manager, process improvement specialist, project manager, or aspiring leader, this course will empower you to lead transformative change initiatives and deliver measurable, sustainable results.

What you’ll learn: 

  • Develop a thorough understanding of Lean Six Sigma principles and advanced techniques.
  • Master the DMAIC methodology and its application to complex process improvement projects.
  • Develop advanced skills in data collection, statistical analysis, and process capability assessment.
  • Learn Lean principles and tools to effectively identify and eliminate waste.
  • Explore proven strategies to sustain improvements through control plans and Lean controls.
  • NOTE: Expect to learn from multiple speakers with diverse backgrounds and experience, ensuring a well-rounded educational experience.

Requirements: 

  • A foundational understanding of basic math concepts.
  • Familiarity with general business and operational concepts.

The Lean Six Sigma Black Belt course is designed by experts to provide you with the advanced skills needed to excel in Lean Six Sigma. Throughout this comprehensive program, you will dive deep into key topics in process improvement and quality management, with a focus on practical, real-world applications. Our expert instructors will guide you through complex concepts and methodologies, ensuring you gain both the knowledge and confidence to implement change.

This course covers essential topics such as Lean Six Sigma principles, the DMAIC methodology, Lean Enterprise, and advanced statistical analysis. You will participate in practical exercises and case studies that reinforce your understanding and build your problem-solving skills. Additionally, the course offers effective strategies for implementing Lean Six Sigma tools, such as design of experiments, regression analysis, and control methods.

Why Choose This Course?
Our Lean Six Sigma Black Belt course is designed with expertise to help you not only understand theory but also apply these principles effectively in the real world. As you progress through the course, you’ll learn from industry experts with years of experience and obtain practical insights that you can apply right away in your professional role. This practical, hands-on learning approach ensures that you’re not just prepared for certification, but ready to lead impactful change and contribute meaningfully to your organization’s success.

Curious about how to make a lasting impact on the world? My courses can equip you with the skills you need.

Our Promise to You

Upon completing this course, you will have the advanced knowledge and practical skills necessary to lead high-impact process improvement initiatives and drive measurable success in your organization.

10 Day Money Back Guarantee. If you are unsatisfied for any reason, simply contact us and we’ll give you a full refund. No questions asked.

Get started today!

Course Curriculum

Section 1 - Course Overview
Course Overview-LSSBB 00:00:00
Section 2 - Lean Six Sigma Introduction
Lean Six Sigma And Process Issues 00:00:00
Section 3 - Six Sigma Overview
Foundation – Introduction 00:00:00
DPMO And Z Score 00:00:00
Example 1 DPMO And Z Score 00:00:00
Example 2 DPMO And Z Score 00:00:00
1.5 Sigma Shift 00:00:00
History Of Six Sigma 00:00:00
History Of Continuous Improvement 00:00:00
Six Sigma Organization 00:00:00
Section 4 - DMAIC Methodology Page
DMAIC Methodology-Six Sigma Methodologies 00:00:00
DMAIC Phases 00:00:00
Example DMAIC Phases 00:00:00
DMAIC Methodology 00:00:00
DMAIC Approach 00:00:00
What A Function Is: Y = f(X) 00:00:00
Six Sigma Success Or Failure 00:00:00
Section 5 - Lean Enterprise
Lean Introduction And History 00:00:00
Lean Approach-01 00:00:00
Lean Approach-02 00:00:00
Lean Approach-03 00:00:00
Example-Jidoka And Quick Changeover 00:00:00
Example-Kanban And Pull Systems And One-Piece Flow 00:00:00
Takt Time And Cycle Time 00:00:00
Value-Added, Non-Value-Added And Waste 00:00:00
Lean Thinking – Add Value 00:00:00
Waste (Muda) 00:00:00
Types Of Waste And Common Causes 00:00:00
Lean Methodology And Tools 00:00:00
Value Stream Mapping (VSM) 00:00:00
5S Or 6S 00:00:00
Kaizen And Types 00:00:00
End Of Module—Summary 00:00:00
Section 6 - Define Phase Overview
Define Phase 00:00:00
Overview 00:00:00
Define Phase – Lean Six Sigma Black Belt 00:00:00
Section 7 - Voice Of Customer (VOC)
VOC Capturing Methods 00:00:00
Kano Analysis 00:00:00
Business Processes 00:00:00
Business Performance Measure (BPM) 00:00:00
Section 8 - Critical To Quality (CTQ)
CTQ 00:00:00
Critical To Quality (CTQ): Flow-Down – CTQ Tree 00:00:00
Translation Of VOC To CTQ 00:00:00
COPQ And 1-10-100 Rule 00:00:00
COPQ 00:00:00
Pareto Chart 00:00:00
Project Primary And Secondary Metrics 00:00:00
Throughput Yield (TPY) 00:00:00
Rolled Throughput Yield 00:00:00
Section 9 - SIPOC Page
SIPOC 00:00:00
Section 10 - Stakeholder Analysis
Stakeholder Analysis 00:00:00
Stakeholder Management 00:00:00
Section 11 - Project Charter
Project Selection 00:00:00
Project Charter 00:00:00
Financial Benefits 00:00:00
Payback Period 00:00:00
Business Case 00:00:00
Project Scope 00:00:00
Project Charter – Summary 00:00:00
Differences Between ARMI And RASIC Tools 00:00:00
Section 12 - Measure Phase Overview
Measure Phase Introduction 00:00:00
Measure Overview 00:00:00
Measure Phase – Lean Six Sigma Black Belt 00:00:00
Section 13 - As-Is Process Review (Process Definition)
Process Map Overview-1 00:00:00
Process Map Overview-2 00:00:00
Type Of Process Mapping 00:00:00
Detailed Process Mapping 00:00:00
Value Stream Mapping (VSM) 00:00:00
VSM – Creation 00:00:00
VSM Common Metrics 00:00:00
VSM – Calculation (Little’s Law) 00:00:00
Value Add Flow Analysis 1 00:00:00
Value Add Flow Analysis 2 00:00:00
Value Add Flow Analysis Exercise 00:00:00
Spaghetti Diagram 00:00:00
X Y Matrix 00:00:00
X Y Matrix Example 00:00:00
5 Whys 00:00:00
5 Whys Example 00:00:00
Fishbone Diagram – 1 00:00:00
Fishbone Diagram – 2 00:00:00
Fishbone Diagram Example 00:00:00
Failure Mode And Effects Analysis (FMEA) 00:00:00
FMEA Other Details 00:00:00
FMEA Template 1 00:00:00
FMEA Template 2 00:00:00
FMEA Rating 00:00:00
FMEA Example 00:00:00
Section 14 - Data Collection And Analysis (Basic Statistics)
Data Collection – Introduction 00:00:00
Data Types 00:00:00
Qualitative Data – Additional Detail 00:00:00
Ranked Data 00:00:00
Operational Definition 00:00:00
Data Stratification 00:00:00
Data Collection Planning 00:00:00
Data Sampling 00:00:00
Data Analysis-Graphical-1 00:00:00
Data Analysis-Graphical-2 00:00:00
Box Plot – Additional Detail 00:00:00
Statistical Analysis – Software 00:00:00
Minitab Introduction 00:00:00
Pulse Example 00:00:00
Pulse Example – Excel 00:00:00
Pulse Example – Histogram 00:00:00
Pulse Example – Box Plot 00:00:00
Pulse Example – Dot Plot 00:00:00
Pulse Example – Stem And Leaf Plot 00:00:00
Pulse Example – Time Series 00:00:00
Pulse Example – Scatter Plot 00:00:00
Data Analysis- Descriptive Statistics 00:00:00
Center Tendency 00:00:00
Center Tendency – Distribution And Data Type 00:00:00
Variability And Dispersion 00:00:00
Symbols For Data 00:00:00
Section 15 - Data Accuracy And Precision (Measurement System Analysis - MSA)
Measurement System Analysis (MSA) – Overview 00:00:00
Measurement System Analysis – Introduction 00:00:00
MSA – Elements 00:00:00
MSA – Elements Exercise 00:00:00
Measurement Error 00:00:00
Measurement Error – Types 00:00:00
Appropriate Measures 00:00:00
Measurement System Analysis (MSA) 00:00:00
MSA – Formula 00:00:00
Percent Tolerance GRR 00:00:00
MSA – Procedure-1 00:00:00
MSA – Procedure-2 00:00:00
MSA – Procedure-3 00:00:00
Example Variable Gage R-R 00:00:00
Example Variable Gage R-R – Excel 00:00:00
Minitab – Variable GRR Methods 00:00:00
Minitab – VGRR 1- Example 00:00:00
Minitab – VGRR 2- Example 00:00:00
Attribute Agreement Analysis 00:00:00
Attribute MSA AAA–Introduction 00:00:00
Attribute MSA – Kappa Statistic 00:00:00
Attribute MSA AAA–Purpose 00:00:00
AAA 1 – Example 00:00:00
AAA 2 – Example 00:00:00
AAA 3 – Example 00:00:00
MSA – Improvement Actions And Summary 00:00:00
Section 16 - Process Capability, Distribution Types, And Stability
Process Capability – Overview 00:00:00
Process Capability – Introduction-I 00:00:00
Process Capability – Introduction-II 00:00:00
Process Capability Analysis 00:00:00
Process Capability – Metrics Cp Cpk Or Pp Ppk 00:00:00
Process Capability – Z Score 00:00:00
IASSC Reference Document – Introduction 00:00:00
Process Capability – Z-Score – Example 00:00:00
Process Capability – Sigma Levels 00:00:00
Process Capability – 1.5 Sigma Shift 00:00:00
Types Of Distributions 00:00:00
Normal Distribution 00:00:00
Example – Normality Test 00:00:00
Example – Process Capability For Normal Data 00:00:00
Non-Normal Data And Transformation 00:00:00
Example – Non-Normal Distribution – Identification 00:00:00
Example – Process Capability For Non-Normal Data 00:00:00
Process Capability – Attribute Data 00:00:00
Binomial And Poisson Process Capability 00:00:00
Binomial Process Capability – Example 00:00:00
Poisson Process Capability – Example 00:00:00
Process Stability– Overview 00:00:00
Control Charts 00:00:00
Process Stability – Example 00:00:00
Process Capability And Stability 00:00:00
End Of Measure Phase Module – Summary 00:00:00
Section 17 - Analyze Phase - Overview
Analyze – Introduction 00:00:00
Analyze Phase – Overview-I 00:00:00
Analyze Phase – Overview-II 00:00:00
Analyze Phase -Lean Six Sigma Black Belt 00:00:00
Section 18 - Patterns Of Variation
Sources-Causes Of Variation 00:00:00
Multi-Vari Chart Analysis 00:00:00
Example: Multi-Vari Chart-I 00:00:00
Example: Multi-Vari Chart-II 00:00:00
Classes Of Distributions 00:00:00
Causes Of Non-Normal Distributions 00:00:00
Non-Normal Distributions: Skewness 00:00:00
Non-Normal Distributions: Kurtosis 00:00:00
Non-Normal Distributions: Multiple Modes And Granularity 00:00:00
Non-Normal Data 00:00:00
Section 19 - Inferential Statistics
Inferential Statistics-Introduction 00:00:00
Confidence Interval 00:00:00
Sampling 00:00:00
Sampling Methods 00:00:00
Example-Sampling 00:00:00
Sample Size 00:00:00
Sampling Bias 00:00:00
Central Limit Theorem (CLT) 00:00:00
Standard Error (SE) 00:00:00
Confidence Interval Of Mean 00:00:00
95 Percent Confidence Interval Of Mean 00:00:00
Confidence Interval-Example 1 00:00:00
Confidence Interval-Example 2 00:00:00
Confidence Interval-Example 2-Excel 00:00:00
Confidence Interval-Example 2-Minitab 00:00:00
Section 20 - Hypothesis Testing
Hypothesis Testing 00:00:00
Six Sigma Project And Hypothesis Testing 00:00:00
Hypothesis And Hypothesis Testing 00:00:00
Significant Differences 00:00:00
Hypothesis Test Options – Normal Data 00:00:00
Hypothesis Test Options – Non-Normal Data 00:00:00
Hypothesis Test Roadmap 00:00:00
Hypothesis Statements Examples 00:00:00
Hypothesis Testing Procedure 00:00:00
P-Value 00:00:00
Risk – Types 00:00:00
Risk – Alpha And Beta 00:00:00
P-Value And Alpha Risk 00:00:00
Statistical Power 00:00:00
Hypothesis Test – In A Nutshell 00:00:00
Section 21 - Hypothesis Testing With Normal Data
Hypothesis Testing With Normal Data 00:00:00
T-Test_Introduction 00:00:00
Example_1-Sample T-Test-V1 00:00:00
Example_1-Sample T-Test-V2 00:00:00
Example_2-Sample T-Test 00:00:00
Example_Paired T-Test-V1 00:00:00
Example_Paired T-Test-V2 00:00:00
Variance Test_Introduction 00:00:00
Example_1- Variance Test-V1 00:00:00
Example_1- Variance Test-V2 00:00:00
Example_2- Variance Test 00:00:00
ANOVA-Introduction 00:00:00
ANOVA-Purpose 00:00:00
ANOVA Test Methods 00:00:00
One-Way ANOVA Table 00:00:00
Example_One-Way ANOVA 00:00:00
Example_One-Way ANOVA_Minitab 00:00:00
Example_Balanced ANOVA-Minitab 00:00:00
Example_Balanced ANOVA-V1 00:00:00
Example_Balanced ANOVA-V2 00:00:00
Example_Balanced ANOVA-V3 00:00:00
Section 22 - Hypothesis Testing With Non-Normal Data
Hypothesis Testing With Non-Normal Data 00:00:00
Nonparametric Tests 00:00:00
One-Sample Sign Test 00:00:00
Example_One-Sample Wilcoxon Test 00:00:00
One-Sample Wilcoxon Signed Rank Test 00:00:00
Example_Test Statistics And Estimated Median 00:00:00
Example_One-Sample Wilcoxon Test-Minitab 00:00:00
Mann-Whitney Test 00:00:00
Example_Mann-Whitney Test 00:00:00
Kruskal-Wallis Test 00:00:00
Example_Kruskal-Wallis Test 00:00:00
Mood’s Median Test 00:00:00
Example_Mood’s Median Test 00:00:00
Friedman Test 00:00:00
Example_Friedman Test 00:00:00
1-Proportion Test 00:00:00
Example: 1-Proportion Test 00:00:00
2-Proportion Test 00:00:00
Example: 2-Proportion Test 00:00:00
Chi-Square Test And Contingency Table 00:00:00
Example: Chi-Square Test-V1 00:00:00
Example: Chi-Square Test-V2 00:00:00
End Of Analyze Phase Module-Summary 00:00:00
Section 23 - Improve Overview
Improve – Introduction 00:00:00
Improve Phase – Overview 00:00:00
Improve Phase – DMAIC Roadmap 00:00:00
Improve Phase – Lean Six Sigma Black Belt 00:00:00
Section 24 - Potential Solutions Generation
Potential Solutions 00:00:00
Solution Or Improvement Hierarchy 00:00:00
Industrial Revolution 4.0 00:00:00
TRIZ-1 00:00:00
TRIZ-2 00:00:00
TRIZ 39 Matrix And 40 Principles 00:00:00
TRIZ Separation Principles 00:00:00
Section 25 - Lean Solutions And Tools
Lean Solutions Most Common Tools 00:00:00
5S Approach-1 00:00:00
5S Approach-2 00:00:00
Visual Factory Management 00:00:00
Kanban-1 00:00:00
Kanban-2 00:00:00
Kanban-3 00:00:00
Jidoka And Andon 00:00:00
Total Productive Maintenance 00:00:00
Quick Changeover 00:00:00
Section 26 - Mistake-Proofing
Mistake-Proofing 00:00:00
Examples Mistake-Proofing 00:00:00
Human Errors 00:00:00
Mistake-Proofing Methods 00:00:00
Section 27 - Select The Best Solution
Select The Best Solution 00:00:00
Assess The Risks 00:00:00
Section 28 - Pilot Implementation
Pilot And Future Map 00:00:00
Standardized Work 00:00:00
Solution Implementation 00:00:00
Section 29 - Simple Linear Regression
Regression Introduction 00:00:00
Correlation 00:00:00
Regression Types 00:00:00
Simple Linear Regression 00:00:00
R-Squared 00:00:00
Example-Simple Linear Regression 00:00:00
Example-SLR—Analysis 00:00:00
Example-SLR—Analysis CI And PI 00:00:00
Residual 00:00:00
Residual—Assumptions 00:00:00
Example-SLR—Residual Plot 00:00:00
Example-SLR-Minitab 00:00:00
Section 30 - Multiple Regression Analysis (MRA)
MRA-Introduction 00:00:00
Nonlinear Data 00:00:00
Example-Polynomial Regression 00:00:00
Nonlinear Data-Transformation 00:00:00
Example Transformation-Minitab 00:00:00
Multiple Linear Regression 00:00:00
MLR-Simple Model 00:00:00
MLR-Complex Model 00:00:00
Nonlinear Regression 00:00:00
Multiple Linear Regression-Steps 00:00:00
Example_MLR—Matrix Plot 00:00:00
Example_MLR—Best Subsets 00:00:00
Example_MLR—ANOVA 00:00:00
Example_MLR—ANOVA (Repeat And Final) 00:00:00
Example_MLR—Residual Analysis 00:00:00
Section 31 - Designed Experiments Or Design Of Experiments (DOE)
DOE Introduction And Objectives 00:00:00
DOE Factors And Levels 00:00:00
DOE Treatments And Combinations 00:00:00
DOE Response Main Effect Interaction 00:00:00
Example-Cooking DOE-V1 00:00:00
Example-Cooking DOE-V2 00:00:00
DOE Multicollinearity 00:00:00
DOE Confounding Variables 00:00:00
DOE Experimental Error 00:00:00
DOE Randomization 00:00:00
DOE Replication 00:00:00
DOE Blocking 00:00:00
DOE Balanced And Orthogonal Designs 00:00:00
DOE Center Points 00:00:00
DOE Design Methods-V1 00:00:00
DOE Design Methods-V2 00:00:00
DOE Design Methods-V3 00:00:00
DOE Design Methods-V4 00:00:00
DOE Create Factorial Design-Example 00:00:00
Section 32 - Full Factorial Experiments
2k Full Factorial Designs 00:00:00
Mathematical Models 00:00:00
Quadratic Mathematical Models 00:00:00
Fit And Diagnose-Overview 00:00:00
Example-2k Full Factorial Design 00:00:00
Example-Create Factorial Design 00:00:00
Example-Analyze Factorial Design-V1 00:00:00
Example-Analyze Factorial Design-V2 00:00:00
Example-Analyze Factorial Design-V3 00:00:00
Example-Analyze Factorial Design-V4 00:00:00
Example-Factorial Plots 00:00:00
Example-Cube Plot 00:00:00
Example-Surface Plot 00:00:00
Example-Contour Plot 00:00:00
Example-Contour Plot Of Cost 00:00:00
Example-Response Optimizer 00:00:00
Fractional Factorial Designs 00:00:00
Confounding Effect 00:00:00
Experimental Resolutions 00:00:00
IP EoM Summary 00:00:00
Section 33 - Control Phase - Overview
Control Phase: Introduction 00:00:00
Control Phase – V1 00:00:00
Control Phase – V2 00:00:00
Control Phase – Lean Six Sigma Black Belt 00:00:00
Section 34 - Lean Controls
Lean Controls 00:00:00
Lean Controls: 5S, Kanban, And Poka-Yoke 00:00:00
Lean Controls: Kaizen 00:00:00
Section 35 - Statistical Process Control
Statistical Process Control 00:00:00
Control Charts 00:00:00
Control Charts: Anatomy 00:00:00
Control Charts: Variation 00:00:00
Control Charts: Decision Rules-V1 00:00:00
Control Charts: Decision Rules-V2 00:00:00
Control Charts: Decision Rules-V3 00:00:00
Control Charts: Types For Continuous Data -V1 00:00:00
Control Charts: Types For Continuous Data -V2 00:00:00
Control Charts: Types For Attribute Data 00:00:00
Control Charts And Decision Rules 00:00:00
Control Charts: I-MR Chart Formulas 00:00:00
Control Charts: X-Bar R Chart Formulas 00:00:00
Control Charts: X-Bar S Chart Formulas 00:00:00
Control Charts: Attributes Chart Formulas-V1 00:00:00
Control Charts: Attributes Chart Formulas-V2 00:00:00
Control Charts: Data Collection 00:00:00
Control Charts Average Run Length 00:00:00
Control Charts: Four States 00:00:00
Control Charts Control Methods 00:00:00
Example: I-MR Chart 00:00:00
Example: X-Bar R Chart 00:00:00
Example: P Chart 00:00:00
Example U Chart 00:00:00
Time-Weighted Control Charts 00:00:00
EWMA Charts 00:00:00
EWMA Charts Formula V1 00:00:00
EWMA Charts Formula V2 00:00:00
EWMA Charts Example 00:00:00
CUSUM Charts 00:00:00
CUSUM Charts Types 00:00:00
CUSUM Charts Example 00:00:00
Section 36 - Six Sigma Control Plan
Control Plans 00:00:00
Implementation Plans 00:00:00
Control Plans Five Elements 00:00:00
Control Plan Preparation 00:00:00
Project Closure 00:00:00
CP EoM Summary 00:00:00

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