Advanced Lean Six Sigma


Advanced Lean Six Sigma Tools and Techniques

What you will learn

Advanced Tools of Lean Six Sigma

Control Charts

Continuous Data Analysis

Descrete Data Analysis

Hypothesis testing

Linear Regression

Description

In this course we will:

  • Review six sigma tools such as PDCA, DMAIC, and SIPOC
  • Review statistics, sampling, and how to use excel to do statistical analysis

We will learn about:

  • Measurement system analysis and attribute agreement analysis
  • The baseline of process performance for discrete data including Yield, DPU, DPMO
  • Statistical process control and control charts, ImR, XbarR, and XbarS charts.
  • Statistical process control charts analysis and how to identify if a process has an issue.
  • The baseline for continuous data and continuous data analyses, sampling distribution, standard error and coefficient of variation, and Z-score, and T-scores
  • Hypothesis testing, confidence interval and central limit theorem, one-sample z-test, t-test, and ANOVA
  • Linear regression, covariance, and correlation, use excel for linear regression analysis
  • At the end of this course, we will complete the Lean Six Sigma project together

This course requires you to be familiar with key concepts of quality and lean six sigma as well as some basic knowledge of statistics.

This course includes multiple examples. Every time a new concept is introduced, I provide real-life examples and how to apply the new concept.


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I will walk you through difficult statistics concepts and will teach you how to use statistical tools and interpret the results of the analysis.

We will use excel, do to all the heavy lifting for us, and our job will be to learn how to apply the tools and understand the results.

I am including all templates and supporting materials and a lot of useful tables that are needed for the analysis, Templates, and tables will be very helpful for you to get started with your lean six sigma project.

English
language

Content

Introduction

Course outline

Introduction

Sig Sigma tools review
Intorduction to statistics
2.3 Introduction to sampling
2.4 Excel Statistics Introduction

3 Measurement System Analysis

3.1 Measurement System Analysis Introduction
3.2 Components of Measuring system
3.3 MSA Example
3.4 MSA Attribute agreement

4 Baseline and Process Performance

4.1 Baseline
4.2 Yield
4.3 DPU AND DPMO

5 Statistical Process Control

5.1 Statistical Process Control
5.2 Individual and Moving Range Control Charts
5.3 XbarR Charts
5.4 XbarS Charts
5.5 Chart Analysis

6 Baseline – Continuous Data

6.1 Continuous data analysis
6.2 Normal distribution and Z score
6.3 Z Score

7 Hypothesis testing

7.1 Confidence interval
7.2 Central Limit Theorem
7.3 Hypothesis Testing
7.4 Hypothesis Testing in Excel
7.5 Thought experiment
7.6 ANOVA

8 Linear Regression

8.1 Covariance & Correlation coefficient
8.2 Regression
8.3 Regression in Excel

9 Project

9.1 Review of the key concepts
9.2 Project review

Final Word

Final Word