Training Agenda

Day

Lesson No.

Topics

1

Introduction

• What people say about CP
• Training types
• Accreditations and Clients
• About Certification Planner
• Introduction to live training
• About the tutorial

Overview of Lean and Six Sigma

• Organizational Objective
• Introduction, Deliverables, and Benefits of Lean Six Sigma Yellow Belt
• Introduction, Deliverables, and Benefits of Lean Six Sigma Green Belt
• Introduction, Deliverables, Benefits of Lean Six Sigma Black Belt
• Profit
• Course Overview

1.0

Define

1.1

Six Sigma: The Basics

• The Meaning of Six Sigma
• Problem-solving strategy
• History of Six Sigma and Continuous Improvement
• Roles and Responsibilities
• Project Team Selection

1.2

Six Sigma: The Fundamentals

• Voice of Customer
• Critical to Quality (CTQ)
• Affinity Diagrams & Pareto Analysis (80:20)
• Cost of Poor Quality
• Six Sigma Projects: DMAIC
• Basic Six Sigma Matrix

1.3

Project Management

• Change
• Project Management Basics
• Business Case and Project Charter
• Cost-Benefit Analysis
• Project Risk Management
• Failure Mode & Effects Analysis (FMEA)

2

1.4

Lean

• Understanding Lean
• Lean: History
• Lean vs 7 Deadly Wastes
• Lean and Six Sigma

2.0

Measure

2.1

Process Definition

• Process Mapping, SIPOC, Value Stream Map
• X-Y Matrix

2.2

Six Sigma Statistics

• Basic Statistics
• Descriptive Statistics
• Distribution and Normality
• Graphical Analysis

2.3

Measurement System Analysis

• Precision & Accuracy
• Accuracy: BIAS, Linearity & Stability
• Variable MSA: GRR
• Stability

2.4

Process Capability

• Capability Analysis
• Attribute and Discrete Capabilities

3

3.0

Analyze

3.1

Patterns of Variation

• Multi-Vari Analysis
• Classes of Distributions

3.2

Inferential Statistics

• Understanding Inference
• Sampling Techniques and Uses

3.3

Hypothesis Testing

• General concepts and goals of Hypothesis testing
• Significance - Practical vs Statistical
• Risk: Alpha & Beta
• Hypothesis Testing
• Reading tables
• Excel: Data Analysis ToolPak
• Testing from Normality

3.4

Hypothesis Testing with Normal Data

• Test of Equal Variance
• Z Tests
• 1 Sample T-Test
• 2 Sample T-Test
• Sample Variance: Chi Square
• One Way Anova
•  

3.5

Hypothesis Testing with Non-Normal Data

• Mann-Whitney
• Kruskal- Wallis
• Mood’s Median
• Friedman
• 1 Sample Sign
• 1 Sample Wilcoxon
• One and two Sample proportion
• Chi-Squared

4

4.0

Improve

4.1

Root Cause Analysis

4.2

Correlation and Linear regression

• Correlation
• Scatter Plot/ X-Y Diagram
• Regression Analysis
• Residuals Analysis
• Multiple Linear Regressions
• Data Transformation, Box, Cox

4.3

Design of Experiments (DOE)

• Designed Experiments
• Full Factorial Experiments
• Fractional Factorial Experiments

4.4

Lean Tools and Practices

• Lean:5s Visual Factory & Standardized work
• Lean: Kaizen, Kanban & Poka-Yoke

5.0

Control

5.1

Statistical Process Control (SPC)

• Data Collection for SPC
• Control Chart Structure and Rules
• I-MR Chart
• Xbar-R Chart
• Xbar-S Chart
• NP-Chart
• P-Chart
• C-Chart
• U-Chart
• CumSum Chart
• EWMA Chart

5.2

Six Sigma Control Plans

• Control Plans

5.3

Lean Controls