Course Outline
Lesson 1: Fundamentals of Six Sigma
Describe Six Sigma
Identify Organizational Drivers and Metrics
Describe Project Selection and Organizational Goals
Describe Lean
Lesson 2: Identifying Six Sigma Methodologies
Describe the DMAIC Methodology
Describe the DFSS Methodology
Describe QFD
Describe DFMEA and PFMEA
Lesson 3: Conducting the Six Sigma Define Phase: Introduction
Describe the Define Phase
Describe Process Elements
Identify Stakeholders and Process Owners
Identify Customers
Gather Customer Data
Analyze Customer Data
Translate Customer Requirements
Identify Six Sigma Projects
Lesson 4: Conducting the Six Sigma Define Phase: Fundamentals of Project Management
Draft a Project Charter
Develop the Project Scope
Identify Project Metrics
Identify Project Planning Tools
Describe Project Documentation
Describe Project Risk Analysis
Describe Project Closure
Lesson 5: Conducting the Six Sigma Define Phase: Management and Planning Tools
Create an Interrelationship Digraph
Create a Tree Diagram
Create a Prioritization Matrix
Describe a Matrix Diagram
Draft a PDPC
Create an Activity Network Diagram
Lesson 6: Conducting the Six Sigma Define Phase: Key Metrics of Projects
Track Process Performance
Perform FMEA
Lesson 7: Conducting the Six Sigma Define Phase: Team Dynamics
Describe Six Sigma Team Stages and Dynamics
Describe Six Sigma Teams and Roles
Identify Team Tools
Identify Effective Communication Techniques
Lesson 8: Conducting the Six Sigma Measure Phase: Introduction
Describe the Measure Phase
Draft a SIPOC
Create a Process Map
Describe Additional Process Documentation Tools
Create a Fishbone Diagram
Create a Cause-and-Effect Matrix
Lesson 9: Conducting the Six Sigma Measure Phase: Probability and Statistics
Describe Basic Probability Concepts
Identify Valid Statistical Conclusions
Describe the Central Limit Theorem
Lesson 10: Conducting the Six Sigma Measure Phase: The Data Collection Plan
Identify Data Types
Identify Data Collection Methods
Identify Sampling Types
Lesson 11: Conducting the Six Sigma Measure Phase: Descriptive Measures
Introduction to Statistical Tools
Compute Descriptive Statistical Measures
Construct Probability Distribution Charts
Describe Other Distributions
Lesson 12: Conducting the Six Sigma Measure Phase: Graphical Methods
Create a Run Chart
Create a Box-and-Whisker Plot
Create a Stem-and-Leaf Plot
Create a Scatter Plot
Create Pareto Charts
Lesson 13: Conducting the Six Sigma Measure Phase: Measurement System Analysis
Perform Measurement System Analysis
Conduct the Gage R&R Study
Interpret Gage R&R Data
Lesson 14: Conducting the Six Sigma Measure Phase: Process Capability and
Performance
Determine Process and Customer Specification Limits
Conduct a Process Capability Study
Interpret Process Capability
Interpret Sigma Levels
Lesson 15: Conducting the Six Sigma Analyze Phase: Introduction
Describe the Analyze Phase
Perform Multi-Vari Studies
Perform Simple Linear Correlation
Perform Simple Regression
Lesson 16: Conducting the Six Sigma Analyze Phase: Hypothesis Testing
Introduction to Hypothesis Testing
Conduct Hypothesis Tests
Perform t-Tests
Perform Single-Factor ANOVA
Perform Chi-Square Tests
Lesson 17: Conducting the Six Sigma Improve Phase
Describe the Improve Phase
Perform DOE
Interpret Main Effects and Interaction Plots
Generate Ideas for Solutions
Pilot Solutions
Lesson 18: Conducting the Six Sigma Control Phase: Introduction
Describe the Control Phase
Draft a Control Plan
Lesson 19: Conducting the Six Sigma Control Phase: SPC
Describe Control Charts
Create Control Charts
Interpret Control Charts
Implement and Validate Solutions
Six Sigma Project Closure
Lesson 20: Describing the Implementation of Six Sigma
Identify the Essentials of Six Sigma Implementation
Describe Six Sigma for Service Industries
Describe DMAIC Failure Modes
Requirements
Six Sigma - Introduction
Testimonials (8)
The pace was just right and the relaxed atmosphere made candidates feel at ease to ask questions.
Rhian Hughes - Public Health Wales NHS Trust
Course - Introduction to Data Visualization with Tidyverse and R
We were using road accident data for practicals
Maphahamiso Ralienyane - Road Safety Department
Course - Statistical Analysis using SPSS
Well thought out and high grade planning materials.
Andrew - Office of Projects Victoria - Department of Treasury & Finance
Course - Forecasting with R
Wasn't boring, the trainer could keep the attention, the topics were covered in depth.
Marta - Ministerstwo Zdrowia
Course - Advanced R Programming
Very tailored to needs.
Yashan Wang
Course - Data Mining with R
The subject matter and the pace were perfect.
Tim - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course - Programming with Big Data in R
At the end of the class, we had a great overview of the language, we were provided tools to continue learning and were provided suggestions on how to continue learning. We covered AI/ML information.
Victor Prado - Global Knowledge Network Training Ltd
Course - R
That Haytham started with the basics and gave us enough time to do the examples and ensure that we were at the same page before we moved on to the next topic.