Course Outline
Introduction to Six Sigma and DMAIC
- Overview of Six Sigma principles
- Understanding the DMAIC process
- Roles and responsibilities of a Green Belt
Define Phase
- Project charter development
- Identifying customer requirements
- Problem statement and project objectives
- High-level process mapping (SIPOC)
Measure Phase
- Data collection strategies
- Measurement System Analysis (MSA)
- Basic statistical analysis
- Process capability Analysis
Analyze Phase
- Root cause analysis techniques
- Exploratory data analysis
- Hypothesis testing
- Identifying and verifying causes
Improve Phase
- Generating and selecting solutions
- Design of Experiments (DOE)
- Implementing improvements
- Risk Analysis and mitigation
Control Phase
- Developing control plans
- Statistical Process Control (SPC)
- Documentation and standardization
- Ensuring sustained improvements
Project Management and Soft Skills
- Effective project management for Green Belts
- Communication and leadership skills
- Team dynamics and conflict resolution
- Change management
Green Belt Certification
- Preparing for the Green Belt certification exam
- Tips and best practices
Summary and Next Steps
Requirements
- Knowledge of Six Sigma principles
- Understanding of basic statistics
Audience
- Managers
- Professionals with Yellow Belt certification
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.