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Free Black belt lean six sigma training

Free IASSC Black Belt Training

Lean Six Sigma

Price

Free

How

Fully online

When

When you want / contents is always available

Main contents of the trainings

  • Expert Lean Six Sigma mastery

  • Leadership in DMAIC implementation

  • Proficiency in advanced statistical analysis and project management

Introduction

Elevate your professional mastery with our Lean Six Sigma Black Belt Training, perfectly in sync with the IASSC's Black Belt Body of Knowledge. This premium training is aimed at those who aspire to the pinnacle of Lean Six Sigma expertise, focusing on comprehensive methodologies and advanced problem-solving skills. By adhering closely to the curriculum detailed on the IASSC website, our course promises not only accuracy and relevance but also an in-depth preparation for the Black Belt certification exam.

The program delves into the extensive aspects of Lean Six Sigma, including advanced DMAIC (Define, Measure, Analyze, Improve, Control) methodologies, complex problem-solving techniques, and leadership skills necessary for managing significant projects and teams. This training is designed to empower you to drive substantial improvements in quality, efficiency, and customer satisfaction within your organization.

 

We encourage you to explore the detailed table of contents for our training, reflecting the IASSC Black Belt Body of Knowledge. Our adherence to these high standards ensures that you receive an education that goes beyond preparing you for certification—it sets you up for real-world success in quality management and process improvement.

Take the definitive step towards becoming a Lean Six Sigma Black Belt, and unlock unparalleled opportunities for career advancement and leadership. Enroll in our Lean Six Sigma Black Belt Training program and become a key driver of excellence in your organization.

For more information on the IASSC and the Black Belt Body of Knowledge, please visit: IASSC Black Belt Body of Knowledge.

Please note that while the training provided here is free, successful completion of the examination requires a fee. Access the examination link here.

Table of content IAASC Black belt

Table of content Google sheet

Here is the Table of Contents for the IASSC Black Belt, which you can access as a Google Doc.
I suggest downloading this Google Sheet and highlighting the cells/articles that you have read.

Table of content links:

0.1 Quick Overview of Lean Six Sigma:

Quick Overview of Lean Six Sigma

Six Sigma Black Belt Salary

Importance of the Black Belt Certification

What to Expect from This Course

IASSC Black Belt vs ASQ Black Belt

ASQ Black Belt Preparation

IASSC Black Belt Preparation

Time Management and Study Tips

Encouragement and Motivational Tips

Common Questions Answered -- BB

How to Give Feedback on the Course

1.0 Define Phase:

Define Phase

1.1 The Basics of Six Sigma

Key Principles of Six SigmaSix

Sigma Methodology Overview

Understanding Process Variability

History and Evolution of Six Sigma

Key people in the history of lean Six Sigma

Deliverables of a Lean Six Sigma Project

The Problem Solving Strategy Y = f(x)

Voice of the Customer

Overview of Six Sigma Belts

Other roles in Six Sigma Projects

1.2 The Fundamentals of Six Sigma:

Overview and Importance of DMAIC in Six Sigma

Definition of Process
Understanding Current Processes

Critical to Quality Characteristics (CTQ’s)

Cost of Poor Quality (COPQ)

Pareto Analysis

List of KPI for Project Selection

1.3 Selecting Lean Six Sigma Projects:

Setting Project Objectives and Scope

Financial Impact and ROI Considerations

Identifying the Problem
Creating a Project Charter

List of KPI for Project Selection

Financial Evaluation & Benefits Capture

1.4 The Lean Enterprise:

Key Principles of Lean

Lean vs. Traditional Management
Employee Engagement and Empowerment
Kaizen (Continuous Improvement)

Origins and Evolution of Lean

“Lean” in Lean Six Sigma
“Six Sigma” In Lean Six Sigma

8 Wastes of Lean

5S

2.0 Measure Phase:

Measure Phase
 

2.1 Process Definition

Data Collection Strategies

Definition of Process

Ishikawa (Fishbone) Diagram

Understanding Current Processes
Value Stream Mapping
Process Mapping
SIPOC

Value-Added and Non-Value-Added Analysis

Scatter Diagram

FMEA
 

2.2 Six Sigma Statistics:

Role of Statistics in Six Sigma
Basic Statistical Concepts
Basic Probability Concepts
Events in Probability

Types of Data

Descriptive Statistics

Normal Distribution

Z-Scores in Process Performance
Z-Scores questions examples
Graphical Analysis

2.3 Measurement System Analysis:

Measurement System Analysis
Importance of Measurement System Analysis in Six Sigma
Validating Measurement Systems
Basic Concepts and Terminology

Assessing Precision and Repeatability

Understanding Accuracy and Bias

Gage Repeatability & Reproducibility

Planning and Conducting a GR&R Study

GR&R Study Example

Variable Measurement Systems
Attribute Measurement Systems

 

2.4 Process Capability:

Process Capability Definition and Importance
Short-term vs. Long-term Capability

Process Capability Indices: Cp, Cpk, Pp, Ppk

Capability Analysis
Process centering

Z-Scores in Process Performance

Z-Scores questions examples

Tools and Techniques for Capability

Evaluating Stability Over Time

Understanding Attribute Data in Process Capability

Tools and Techniques for Capability Analysis with Attributes Data

Monitoring Techniques

Strategies for Improving Process Capability

3.0 Analyze Phase

Analyze Phase

3.1 Patterns of Variation

Distinguishing Between Common and Special Causes

Trend PatternPoint Outlier

Strategies for Common Cause

VariationStrategies for

Special Cause Variation

Process Adjustment and Improvement

Multivariate Analysis Techniques

Key Probability Distributions

Gamma Distribution

ExponentialDistribution

Poisson Distribution

Chi-Squared Distribution

Weibull Distribution

Logistic Distribution

Binomial Distribution

Normal DistributionBeta

DistributionTriangular Distribution

3.2 Inferential Statistics

Overview of Inferential Statistics in Six Sigma

Role of Inferential Statistics in Decision Making

Basics of Probability Theory

Key Probability Distributions

3.3 Hypothesis Testing

Definition and Purpose of Hypothesis Testing

Data Analysis and Hypothesis Testing

Statement of Hypotheses

Selection of Significance Level (α)

Detailing Beta

Choice of Test Statistic

Decision Rule Based on P-value or Critical Value

Null Hypothesis (H0)

Alternative Hypothesis (H1)

Type I Error (False Positive)

Type II Error (False Negative)

Power of the Test

Significance; Practical vs. Statistical

Selection of Significance Level (α)

Detailing Beta

Selecting the Right Test

3.4 Hypothesis Testing with Normal Data

Selecting the Right Test

Characteristics of Normal Distribution

Normality Tests

One-Sample t-Test

t-Test (Independent)

t-Test (Dependent)

Two-Sample T-Test

Test for Variance

Comparing Two Variances

One-Way ANOVA

3.5 Hypothesis Testing with Non-Normal Data

Selecting the Right Test

Handling Non-Normal Data

Significance of Non-Normal Data in Process Improvement

Basic Concepts and Terminology

Identifying Non-Normal Data

Causes and Implications of Non-Normality

Formulating Hypotheses for Non-Normal Data

Mann-Whitney U Test

Kruskal-Wallis Test

Median Test

Friedman Test

Signed-Rank Test

Wilcoxon Signed-Rank Test

Independent Samples Analysis

Paired Samples Analysis

Chi-Square Test for Independence

Robust Hypothesis Testing

Common Challenges in Non-Normal Hypothesis Testing

Best Practices for Reliable Results

4.0 Improve Phase

Improve Phase

4.1 Simple Linear Regression

Importance in Lean Six Sigma - Overview of Regression Types

Definition and Key Concepts - Role in Predictive Modeling

Regression Analysis

Hypothesis Testing with Regression Analysis

Linearity - Homoscedasticity - Normality - Independence

Understanding Correlation

Pearson and Spearman Correlation

CoefficientsCorrelation Coefficient Test

Factor Analysis

Step -by -Step Model Building Process

Diagnosing Model Fit - Residual Analysis

Handling Missing Data and Outliers

4.2 Multiple Regression Analysis

Multiple Regression Analysis

Model Building in Multiple Regression

Overview of Regression Types

Conceptual Differences from Simple Regression - Benefits and Complexities

Types of Variables: Continuous, Categorical - Incorporating Interaction Terms

Validation Approaches - Prediction Accuracy Measures

Diagnosing Model Fit - Residual Analysis

Data Transformation Techniques

Box-Cox Transformation

4.3 Designed Experiments

DOE Key Principles

Overview of Design Types - Choosing the Right Design for Your Study

Experiment Objectives

Steps in Planning - Execution Best Practices

Handling Constraints in Design

4.4 Full Factorial Experiments

Concept and Importance

Factors and Levels Selection - Sample Size Considerations

Linear & Quadratic Mathematical Models

Balanced & Orthogonal Designs

Fit, Diagnose Model and Center Points

4.5 Fractional Factorial Experiments

Design Resolutions

Selecting Factors and Fractions - Alias Structure and Its Implications

Identifying Significant Factors - Interaction Effect Analysis

Confounding and Its Resolution

Mixed-Level Designs

Response Surface Methodology (RSM)

Taguchi Methods in Fractional Factorial Designs

Real -world Applications in Lean Six Sigma Projects

5.0 Control Phase:

Control Phase

5.1 Lean Controls

Definition and Importance of Lean Controls

Principles of Lean Thinking in Control Systems

Visual Management Systems

Implementation of Visual Control

ToolsBenefits of Visual Management

5S

Continuous Improvement and Auditing

Sustaining Lean in the Long Term

Designing Kanban Systems

Poka-Yoke (Error Proofing)

Techniques and Examples of Poka-Yoke

5.2 Statistical Process Control (SPC)

Definition and Importance of SPC in Six Sigma

Historical Background of SPC

The Concept of Control Charts

Selecting the Right Type of Chart

Data Collection Techniques

Variable Data Control Charts

Attribute Data Control Charts

List of control chart

Individual-Moving Range (I-MR) Chart

X-bar and R Chart

U Chart (Defects per Unit Chart)

P Chart (Proportion Chart)

NP Chart (Number Defective Chart)

X-bar and S Chart

CUSUM Chart (Cumulative Sum Control Chart)

EWMA Chart (Exponentially Weighted Moving Average)

Steps to Implement Control Charts

Constructing a Control Chart

SPC Terminology

Establishing Control Limits

5.3 Six Sigma Control Plans:

Purpose and Importance in Six Sigma
Developing Control Plans

Cost Benefit Analysis

Overview of Control Plan Components
Setting Control Limits
Use of Control Charts

Elements of the Response Plan

Response Plans for Process Deviations

6.0 Extra notes

List of Terms and Definitions

Learn how to Read Exam charts

Overview of the Certification Exams

The ASQ Black Belt Exam

The IASSC Lean Six Sigma Black Belt Exam

Cheat Sheets and Quick Reference Guides

The Two Most Important Charts in Lean Six Sigma

Mock Exams and Practice Questions

Exam Preparation Strategies

Handling Exam Anxiety and Stress

Exam Rules and Protocols

Post-Exam Steps: What to Do After the Exam

Continuing Education and Next Steps in Your Lean Six Sigma Journey

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