Lean Six Sigma Black Belt Certification Training

Six Sigma Black Belt Course Overview

This Lean Six Sigma Black Belt training and certification course is designed to help you master the combined concepts of Lean and Six Sigma. This course will help you develop an in-depth understanding of the Six Sigma phases Define, Measure, Analyze, Improve and Control (DMAIC) and how to maximize customer value while minimizing waste.

What you'll learn

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  • Learn Research
  • Collect Usefull Data
  • Requirement Analysis Phase
  • Market competent Skills
  • Problem Solving Skills
  • Model Implementation Skills
  • Building or Developing Phase
  • Presenting and Testing Skills

    Course Includes:

  • 7+ hours on-demand video
  • 7+ articles
  • 20+ downloadable resources
  • Full access
  • Access on mobile and TV
  • Certificate of completion

Benefits

Whether you work for a small company, a large corporate or from home, a computer will be one of the first pieces of office equipment you’re going to need. And they comes in different forms, such as laptops and desktops. Computer skills are a valuable addition to any employee’s personal portfolio. Upskilling and polishing your computer literacy can greatly increase your desirability to employers. This is the perfect opportunity to take on roles you might not have previously considered. As an employer, motivating your employees to become computer literate will increase productivity and also stave off problems that can cost time and significant amounts of money. Many companies have started to depend upon computerised technology to get work done. Which is why computer skills have become increasingly important. Having the necessary and basic computer course knowledge will put you a step ahead of others. You’ll have a big advantage over those who aren’t computer literate. It’s for this specific reason that many schools and tertiary institutions encourage students to complete basic computer studies. Here are three reasons why being computer literate is beneficial in the workplace.

Helping professionals thrive, not just survive

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Learning — Blended to Perfection

Learning — Blended to Perfection

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Six Sigma Black Belt Course Curriculum

Eligibility

This Black Belt Six Sigma certification course is suitable for people who are senior managers, team leaders, software professionals, project managers, quality assurance engineers, and management professionals.

Pre-requisites

There are no prerequisites required in order to sit for the IASSC Certified Lean Six Sigma Black Belt Exam. To be successful during the exam, formal Lean Six Sigma training is recommended from a verified Lean Six Sigma trainer or corporate program. It is also recommended that those appearing the exam have some degree of real-world Lean Six Sigma work experience.

Course Content

Section 00 - Six Sigma Black Belt
0.1 Welcome
0.2 Six Sigma Black Belt
0.3 Agenda
0.4 What is SSBB
0.5 Accreditation Institute
0.6 Target Audience
0.7 SSBB Exam Format
0.8 Simplilearn LSSBB Course Offer
0.9 Thank You
Section 01 - Overview
1.1 Welcome
1.2 Overview
1.3 Agenda
1.4 Lesson 1 About LSSBB
1.5 Agenda
1.6 What is Six Sigma
1.7 Six Sigma Roles and Responsibilities
1.8 About SSBB
1.9 LSSBB Roles and Responsibilities
1.10 Summary
1.11 Lesson 2 Organizational Roadblocks
1.12 Agenda
1.13 Traditional Organization versus Customer Driven Organization
1.14 Types of Organizational Roadblocks
1.15 Types of Organizational Roadblocks(Contd.)
1.16 Types of Organizational Roadblocks(Contd.)
1.17 Types of Organizational Roadblocks(Contd.)
1.18 Types of Organizational Roadblocks(Contd.)
1.19 Types of Organizational Roadblocks(Contd.)
1.20 Types of Organizational Roadblocks(Contd.)
1.21 Change Resistance Curve
1.22 Change Resistance Curve(Contd.)
1.23 Change Resistance Curve(Contd.)
1.24 Common Resistance Points
1.25 Common Resistance Points(Contd.)
1.26 Overcoming Resistance Points
1.27 Force Field Analysis
1.28 Force Field Analysis(Contd.)
1.29 Force Field Analysis(Contd.)
1.30 Force Field Analysis(Contd.)
1.31 Summary
1.32 Lesson 3 Role of Communication and Selection Criteria in Black Belt
1.33 Agenda
1.34 Black Belt Role Summary
1.35 Black Belt Communication Expectations
1.36 Black Belt Selection Criteria
1.37 Summary
1.38 Lesson 4 Overview of Continuous Improvement
1.39 Agenda
1.40 Continual Improvement Process
1.41 Continuous versus Continual Improvement
1.42 Kaizen Continual Improvement
1.43 Kaizen Continual Improvement(Contd.)
1.44 Summary
1.45 Lesson 5 Lean An Overview
1.46 Agenda
1.47 What is Lean
1.48 History of Lean
1.49 Principles of Lean
1.50 Key Benefits of Implementing Lean
1.51 Key Benefits of Implementing Lean(Contd.)
1.52 Why Lean before Six Sigma
1.53 Summary
1.54 Lesson 6 Lean Concepts Explained
1.55 Agenda
1.56 Warusa Kagen
1.57 Warusa Kagen(Contd.)
1.58 3Ms
1.59 8 Types of Waste (TIMWOODS)
1.60 Mottainai
1.61 Hoshin Kanri
1.62 Hoshin Kanri(Contd.)
1.63 Hoshin Kanri(Contd.)
1.64 Takt Time
1.65 Takt Time(Contd.)
1.66 Cycle Time
1.67 Lead Time
1.68 Lead Time Assignment
1.69 Lead Time Assignment(Contd.)
1.70 Production Cycle Efficiency
1.71 Batch Size
1.72 Every Part Every Interval(EPEI)
1.73 EPEI(Contd.)
1.74 EPEI(Contd.)
1.75 EPEI Calculation Spreadsheet
1.76 Batch Size Assignment
1.77 Batch Size Assignment(Contd.)
1.78 Batch Size Assignment(Contd.)
1.79 Batch Size Assignment(Contd.)
1.80 Batch Size Assignment(Contd.)
1.81 Crew Size
1.82 Crew Size Assignment
1.83 Crew Size Assignment(Contd.)
1.84 Crew Size Assignment(Contd)
1.85 Standardized Working Progress(SWIP)
1.86 Summary
1.87 Lesson 7 Lean Tools Explained
1.88 Agenda
1.89 5S
1.90 5S(Contd.)
1.91 5S Audit Worksheet
1.92 SMED
1.93 SMED(Contd.)
1.94 Heijunka
1.95 Heijunka An Example
1.96 Genchi Genbutsu
1.97 Value Stream Mapping(VSM)
1.98 VSM Symbols
1.99 Value Stream Mapping(Contd.)
1.100 Value Stream Mapping(Contd.)
1.101 Summary
1.102 Quiz
1.103 Thank You
Section 02 - DFSS, Pre-define and Define (DMAIC)
2.1 Welcome
2.2 Agenda
2.3 DFSS Pre Define and Define(DMAIC)
2.4 DFSS Design for Six Sigma and DMAIC versus DFSS
2.5 Agenda
2.6 Agenda(Contd.)
2.7 Design for Six Sigma(DFSS)
2.8 DFSS Approach to Problem Solving
2.9 DMAIC Approach to Problem Solving
2.10 DMAIC versus DFSS
2.11 DFSS Tools
2.12 Toll Gate Review
2.13 Benchmarking
2.14 MSA
2.15 VOC
2.16 Needs Vs Requirements
2.17 KJ Diagram
2.18 Quality Function Deployment(QFD)
2.19 Kano Model
2.20 Kano Model(Contd.)
2.21 Kano Model(Contd.)
2.22 HOQ
2.23 HOQ(Contd.)
2.24 HOQ(Contd.)
2.25 AHP
2.26 AHP(Contd.)
2.27 Pugh Matrix for Concept Selection
2.28 Pugh Matrix for Concept Selection(Contd.)
2.29 Sample Pugh Matrix
2.30 Monte Carlo Simulation
2.31 Design for X
2.32 Summary
2.33 Lesson 2 Pre Define Activities
2.34 Agenda
2.35 Prerequisites of a Six Sigma Project
2.36 Qualifications of a Six Sigma Project
2.37 Cornerstones of a Six Sigma Project
2.38 Six Sigma Deployment Cycle Plan
2.39 10 Point Ongoing Project Evaluation
2.40 Project Prioritization Matrix
2.41 Project Prioritization Matrix(Contd.)
2.42 Enterprise Wide versus LOB View
2.43 Enterprise Wide Roles and Responsibilities
2.44 NPV(Net Present Value)
2.45 Internal Rate of Return(IRR)
2.46 NPV and IRR An Example
2.47 NPV and IRR An Example(Contd.)
2.48 Summary
2.49 Lesson 3 Define
2.50 Agenda
2.51 Define Key Objectives
2.52 Voice of Customer
2.53 Voice of Business
2.54 Voice of Process
2.55 VOC VOB and VOP
2.56 Kano Model
2.57 Assignment
2.58 Translation to Project Y
2.59 Quality Function Deployment
2.60 Quality Function Deployment(Contd.)
2.61 Quality Function Deployment An Example
2.62 Process Map
2.63 Y Baseline Performance
2.64 Y Baseline Performance(Contd.)
2.65 SIPOC
2.66 Project Charter
2.67 The Problem Statement and the Goal Statement
2.68 RACI Matrix
2.69 Business Metrics
2.70 Business Metrics(Contd.)
2.71 Project Deliverables
2.72 Project Scheduling
2.73 Team Selection
2.74 Define Roles and Responsibilities
2.75 Define Tools Summary
2.76 Lesson 3 Summary
2.77 Quiz
2.78 Thank You
Section 03 - Measure
3.1 Measure
3.2 Introduction to MEASURE
3.3 Agenda
3.4 Pre Measure Considerations and Tools
3.5 Agenda
3.6 Define Phase Toll Gate Review
3.7 DFMEA
3.8 DFMEA(Contd.)
3.9 DFMEA(Contd.)
3.10 DFMEA(Contd.)
3.11 DFMEA(Contd.)
3.12 Cause and Effect Matrix(CE Matrix)
3.13 Cause and Effect Matrix(Contd.)
3.14 Cause and Effect Matrix(CE Matrix)(Contd.)
3.15 Cause and Effect Matrix(CE Matrix)(Contd.)
3.16 Cause and Effect Matrix(CE Matrix)(Contd.)
3.17 Cause and Effect Matrix(Contd.)
3.18 Summary
3.19 Types of Data and Measurement Scales
3.20 Agenda
3.21 Objectives of Measure Phase
3.22 What is a Process
3.23 Flowcharts
3.24 SIPOC
3.25 SIPOC(Contd.)
3.26 SIPOC(Contd.)
3.27 Metrics
3.28 Measurement Scales
3.29 Measurement Scales(Contd.)
3.30 Measurement Scales(Contd.)
3.31 Types of Data
3.32 Types of Data(Contd.)
3.33 Summary
3.34 Central Tendency and Dispersion
3.35 Agenda
3.36 Central Tendency and Dispersion Introduction
3.37 Mean
3.38 Mean(Contd.)
3.39 Median
3.40 Mode
3.41 Range
3.42 Variance
3.43 Standard Deviation
3.44 Mean Deviation
3.45 Summary
3.46 Measurement System Analysis
3.47 Agenda
3.48 Purpose of Measurement System Analysis
3.49 Measurement System Errors
3.50 Measurement System Errors(Contd.)
3.51 Measurement System Errors(Contd.)
3.52 Properties of Good Measurement Systems
3.53 Measurement System Errors Illustrated
3.54 Measurement System Discrimination
3.55 Bias
3.56 Bias(Contd.)
3.57 Measurement System Analysis Process Flow
3.58 Part Variation
3.59 Measurement System Analysis Formulas
3.60 Measurement Systems Analysis Example
3.61 Measurement Systems Analysis Example(Contd.)
3.62 Measurement Systems Analysis Graphs
3.63 Measurement Systems Analysis Graphs(Contd.)
3.64 Measurement Systems Analysis Graphs(Contd.)
3.65 Assignment
3.66 Attribute RR
3.67 Attribute RR(Contd.)
3.68 Attribute RR(Contd.)
3.69 Attribute RR(Contd.)
3.70 Attribute RR(Contd.)
3.71 Attribute RR(Contd.)
3.72 Attribute RR(Contd.)
3.73 Attribute RR(Contd.)
3.74 Attribute RR(Contd.)
3.75 Attribute RR(Contd.)
3.76 When to Do Measurement System Analysis
3.77 Data Collection Plan
3.78 Data Collection Plan Template and Example
3.79 Summary
3.80 Stability Conditions
3.81 Agenda
3.82 Controlled Process and Variation
3.83 Special Causes of Variation
3.84 Common Causes of Variation
3.85 Common Causes of Variation(Contd.)
3.86 Stability Introduction and SPC
3.87 Stability Check with Minitab
3.88 Stability Check with Minitab(Contd.)
3.89 Stability Check with Minitab(Contd.)
3.90 Stability Check with Minitab(Contd.)
3.91 Stability Check using Run Charts
3.92 Stability Conditions
3.93 Central Limit Theorem
3.94 Summary
3.95 Capability Metrics
3.96 Agenda
3.97 Process Capability Pre Considerations
3.98 Process Capability Pre Considerations(Contd.)
3.99 Process Capability Pre Considerations(Contd.)
3.100 Process Capability Pre Considerations(Contd.)
3.101 Process Capability Pre Considerations(Contd.)
3.102 Process Capability Pre Considerations(Contd.)
3.103 Process Capability Pre Considerations(Contd.)
3.104 Process Capability Pre Considerations(Contd.)
3.105 Process Capability Pre Considerations(Contd.)
3.106 Process Capability Indices for Continuous Data
3.107 Process Capability Indices for Continuous Data(Contd.)
3.108 Process Capability Indices for Continuous Data(Contd.)
3.109 Process Capability Indices Interpretation
3.110 Process Capability for Discrete Data
3.111 Process Capability for Discrete Data(Contd.)
3.112 Process Capability for Discrete Data(Contd.)
3.113 Non Normal Capability Analysis
3.114 Non Normal Capability Analysis(Contd.)
3.115 Non Normal Capability Analysis(Contd.)
3.116 Non Normal Capability Analysis(Contd.)
3.117 Non Normal Capability Analysis(Contd.)
3.118 Non Normal Capability Analysis(Contd.)
3.119 Assignment
3.120 Summary
3.121 Variations Variability Capability and Process Conditions
3.122 Agenda
3.123 Variations and Variability
3.124 Variations and Variability(Contd.)
3.125 Variations and Variability(Contd.)
3.126 Capability and Process Conditions
3.127 Summary
3.128 Data Distributions
3.129 Agenda
3.130 Permutations and Combinations
3.131 Permutations and Combinations(Contd.)
3.132 Frequency and Cumulative Distributions
3.133 Binomial Distribution
3.134 Binomial Distribution(Contd.)
3.135 Binomial Distribution(Contd.)
3.136 Binomial Distribution(Contd.)
3.137 Poisson Distribution
3.138 Poisson Distribution(Contd.)
3.139 Poisson Distribution(Contd.)
3.140 Normal Distribution
3.141 Normal Distribution(Contd.)
3.142 Exponential Distribution
3.143 Exponential Distribution
3.144 Summary
3.145 Sigma Shift Mean Shift and Reducing Variations
3.146 Agenda
3.147 Sigma Shift
3.148 Mean Shift or Reducing Variations
3.149 Mean Shift or Reducing Variations(Contd.)
3.150 Baseline Data
3.151 Summary
3.152 Measure Phase Summary
3.153 Measure Activity Summary
3.154 Measure Tools Summary
3.155 Quiz
3.156 Thank You
Section 04 - Analyze
4.1 Welcome
4.2 Analyze
4.3 Agenda
4.4 Lesson 1 Pre Analyze Considerations
4.5 Agenda
4.6 Analyze Phase Introduction
4.7 Pre Analyze Considerations
4.8 Pre Analyze Considerations(Contd.)
4.9 Objectives of Analyze
4.10 Visually Displaying Data
4.11 Summary
4.12 Lesson 2 Value Stream Analysis
4.13 Agenda
4.14 Value Waste and NVA Activities
4.15 What is a Value Stream
4.16 Value Stream Example
4.17 Value Stream Analysis Muda
4.18 Value Stream Analysis Muda(Contd.)
4.19 Value Stream Map
4.20 Value Stream Map(Contd.)
4.21 Spaghetti Charts
4.22 Spaghetti Chart As Is
4.23 Spaghetti Chart Should Be
4.24 Spaghetti Charts(Contd.)
4.25 Summary
4.26 Lesson 3 Sources of Variation
4.27 Agenda
4.28 Sources of Variation
4.29 Sources of Variation(Contd.)
4.30 Cause and Effect Diagram
4.31 Cause and Effect Diagram(Contd.)
4.32 Cause and Effect Diagram(Contd.)
4.33 Cause and Effect Diagram(Contd.)
4.34 Affinity Diagram
4.35 Box Plot
4.36 Box Plot (Contd.)
4.37 Box Plot(Contd.)
4.38 Box Plot(Contd.)
4.39 Box Plot(Contd.)
4.40 Summary
4.41 Lesson 4 Regression
4.42 Agenda
4.43 Objectives of Regression Analysis
4.44 Concepts of Regression Analysis
4.45 Concepts of Regression Analysis(Contd.)
4.46 Simple Linear Regression
4.47 Simple Linear Regression(Contd.)
4.48 Simple Linear Regression(Contd.)
4.49 Simple Linear Regression(Contd.)
4.50 Simple Linear Regression(Contd.)
4.51 Simple Linear Regression(Contd.)
4.52 Multiple Linear Regression
4.53 Multiple Linear Regression(Contd.)
4.54 Multiple Linear Regression(Contd.)
4.55 Multiple Linear Regression(Contd.)
4.56 Multiple Linear Regression(Contd.)
4.57 Multiple Linear Regression(Contd.)
4.58 Multiple Linear Regression(Contd.)
4.59 Multiple Linear Regression(Contd.).mp4
4.60 Multiple Linear Regression(Contd.)
4.61 Best Subsets Regression and Stepwise Regression
4.62 Summary
4.63 Lesson 5 Confidence Intervals
4.64 Agenda
4.65 Concepts of Confidence Intervals and Confidence Intervals Testing
4.66 Concepts of Confidence Intervals and Confidence Intervals Testing(Contd.)
4.67 Concepts of Confidence Intervals and Confidence Intervals Testing(Contd.)
4.68 Concepts of Confidence Intervals and Confidence Intervals Testing(Contd.)
4.69 Confidence Intervals for Difference between Two Means
4.70 Confidence Intervals Working
4.71 Confidence Intervals Working(Contd.)
4.72 Confidence Intervals Impactors
4.73 Chi Square Confidence Intervals for Variances
4.74 Chi-Square Confidence Intervals for Variances(Contd.)
4.75 Z Confidence Intervals for Proportions
4.76 Chi Square and Probability
4.77 T Distribution Confidence Intervals
4.78 Summary
4.79 Lesson 5 Parametric Hypothesis Testing
4.80 Agenda
4.81 Agenda(Contd.)
4.82 Hypothesis Testing Objective
4.83 Hypothesis Testing Concepts
4.84 Null and Alternate Hypothesis
4.85 Type 1 Error
4.86 Type II Error
4.87 Significance Level (?)
4.88 Significance Level (?) (Contd.)
4.89 Type II Error (Contd.)
4.90 ? and Power
4.91 P Value, and Acceptance and Rejection Conditions
4.92 Sample Size Determination for Tests
4.93 1 Sample z Test
4.94 1 Sample z Test(Contd.)
4.95 1 Sample z Test(Contd.)
4.96 2 Sample z test
4.97 f Test of Equality of Variances
4.98 1 Sample t Test
4.99 1 Sample t Test(Contd.)
4.100 2 Sample t Test
4.101 2 Sample t Test
4.102 2 Sample t Test
4.103 Paired t Test
4.104 Paired t Test(Contd.)
4.105 Paired t Test Interpretation
4.106 Paired t Test(Contd.)
4.107 Paired t Test(Contd.)
4.108 ANOVA
4.109 One Way ANOVA
4.110 Two Way ANOVA with Replication
4.111 Two Way ANOVA with Replication(Contd.)
4.112 Two Way ANOVA with Replication(Contd.)
4.113 Two Way ANOVA with Replication(Contd.)
4.114 Summary
4.115 Lesson 7 Nonparametric Hypothesis Testing
4.116 Agenda
4.117 Nonparametric Testing Conditions
4.118 Mann Whitney Test
4.119 Mann Whitney Test(Contd.)
4.120 1 Sample Sign
4.121 Wilcoxon Sign Rank Test
4.122 Kruskal Wallis
4.123 Mood?? Median
4.124 Friedman ANOVA
4.125 Friedman ANOVA(Contd.)
4.126 Summary
4.127 Lesson 8 Analyze Additionals Categorical Data and Current Reality Tree
4.128 Agenda
4.129 Categorical Data Analysis
4.130 Categorical Data Analysis(Contd.)
4.131 Categorical Data Analysis(Contd.)
4.132 Categorical Data Analysis(Contd.)
4.133 Current Reality Tree
4.134 Current Reality Tree(Contd.)
4.135 Summary
4.136 Activity Summary Analyze
4.137 Tools Summary Analyze
4.138 Quiz
4.139 Thank You
Section 05 - Improve
5.1 Welcome
5.2 Section V Improve
5.3 Agenda
5.4 Section V Lesson 1
5.5 Agenda
5.6 Pre Improve Considerations
5.7 Model Adequacy Checking
5.8 Model Adequacy Checking(Contd.)
5.9 Model Adequacy Checking(Contd.)
5.10 Multi Vari Charts
5.11 7M Tools
5.12 Activity Network Diagram
5.13 Point and Interval Estimation
5.14 Porter s Five Forces
5.15 Porter s Five Forces (Contd.)
5.16 Pugh Analysis
5.17 Lean 5S
5.18 Summary
5.19 Section V Lesson 2 Design of Experiments Theory
5.20 Agenda
5.21 Introduction to DOE
5.22 Introduction to DOE(Contd.)
5.23 Introduction to DOE(Contd.)
5.24 Introduction to DOE(Contd.)
5.25 Introduction to DOE(Contd.)
5.26 Introduction to DOE(Contd.)
5.27 Types of Designed Experiments
5.28 Main and Interaction Effects
5.29 Main and Interaction Effects(Contd.)
5.30 Main and Interaction Effects(Contd.)
5.31 Main and Interaction Effects(Contd.)
5.32 Replication
5.33 Randomization
5.34 Blocking
5.35 Confounding
5.36 Coding

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