Course Description
The training is organized around the five main phases of the Six Sigma Process Improvement Roadmap: Define, Measure, Analyze, Improve, and Control (DMAIC). Candidates participate in four training sessions, with at least three weeks in between, allowing them to apply the material learned to their project.
For project-based training, project reviews during each training session maintain project focus. In this case, it is the responsibility of the Champion to ensure that their Belt candidates arrive at class with a proper project charter.
Optional: In between training, QSG can provide coaching and guidance to ensure that the methodology and roadmap are used appropriately. This is a separate service provided apart from this 160-hour training program.
Who Should Attend
This course is designed for process, product, and quality engineers who will lead project teams to achieve quality, yield, and productivity improvements. The Black Belts will normally lead complex production process related problems which may transcend across several processes and/or departments within an organization.
Learning Objectives
Through training, participants will:
- Know the process improvement roadmap DMAIC to systematically define, measure, analyze, improve, and finally control the process
- Know how to identify projects and define the project charter
- Achieve an in-depth understanding of the knowledge based and data based (statistical) methods and tools to characterize and baseline the process
- Be able to perform Multi-Vari studies to determine the various sources of noise in the process
- Be able to design experiments to screen, characterize, and optimize the process with respect to controllable process factors
- Know about various control methods to ensure that the improvement achieved is sustained
Course Outline
Week/Phase | Project Objective | Topics |
Week 1
(40 hrs) Define/ |
|
Introduction to Six Sigma
DMAIC/DMADV Roadmaps Project Scoping and Chartering SIPOC/Process Mapping Cause and Effect Matrix Introduction to Minitab or JMP Basic Statistics Basic Quality Tools Central Limit Theorem Introduction to SPC Variables & Attribute Measurement System Analysis (MSA) Capability Study Initial Control Plan Project Review |
Week/Phase | Objectives | Topics |
Week 2
(40 hrs) Analyze |
|
Review of Week 1
Introduction to Multi-Vari Study Hypothesis Testing Confidence Intervals One and Two Sample Comparisons
Three or more Sample Comparison
Simple Regression Multiple Linear Regression Chi Square Test Non-Parametric Tests for Medians Sample Size Determination Failure Mode and Effects Analysis Project Review |
Week/Phase | Objectives | Topics |
Week 3 (40 hrs) Analyze/ |
|
Review of Week 2
Logistic Regression for Attribute Response Model Building
Introduction to DOE and Attributes of a well-designed experiment General Factorial Designs
2k Designs
Fractional Factorial Screening Designs
Live Experimentation Project Review |
Week/Phase | Objectives | Topics |
Week 4
(40 hrs) Improve/ |
|
Review of Week 3
Designs with Center points Introduction to Response Surface Methods
Multiple Response Optimization
Sequential Experimentation DOE Planning Live Experimentation Evolutionary Methods Introduction to Taguchi Methods Intermediate SPC Total Control Methodology Poka-Yoke (Mistake-Proofing) Final Control Plan Closing Projects Project Reviews |
Prerequisites
None
Course Format
160 hours
Instructor-led class training, with opportunities to practice learned skills using prepared data, live demonstrations, and data collected real time in class
Minitab or JMP Statistical Software
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