Six Sigma DMAIC Full Outline

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The OSSS Six Sigma DMAIC course (Version 8.1) is comprised of:

1,215 slides
Instructor notes
Slide explanations
36 data sets
20 supporting templates

Define

Phase Description:
The Define section of the DMAIC methodology is constructed to introduce the core fundamentals of Six Sigma. There are 5 modules in this phase.

Understanding Six Sigma (37 Slides)
Deliverables
Describe the objectives of Six Sigma
Describe the relationship between variation and sigma
Recognize some Six Sigma concepts
Recognize the Six Sigma implementation model
Describe your role and responsibilities in Six Sigma

Six Sigma Fundamentals (36 Slides)
Deliverables
Describe what is meant by "Process Focus"
Describe the importance of VOC, VOB, and VOE, and CTQ's
Explain COPQ
Generate a Process Map
Describe the Basic Six Sigma metrics
Explain the difference between FTY and RTY
Explain the difference between DPU and DPMO

Selecting Projects (41 Slides)
Deliverables
Utilize a structured approach to select projects
Refine and Define the problem into a project charter
Make an initial estimate of your projects benefits

Elements of Waste (19 Slides)
Deliverables
Have a clear understanding of the specific deliverables
Have started to develop a project plan to meet the deliverables
Have identified ways to deal with potential roadblocks
Be ready to apply the Six Sigma method through your project

Wrap Up & Action Items (9 Slides)

Measure

Phase Description:
The Measure section of the DMAIC methodology is constructed to introduce important Six Sigma tools for characterizing your business issues. There are 6 modules in this phase.

Welcome to Measure (4 Slides)

Process Discovery (81 Slides)
Deliverables
Create a high level process map
Create a Fishbone Diagram
Create an XY Diagram
Describe the elements of a FMEA
Explain the importance of a FMEA
Describe why each tool is important

Six Sigma Statistics (59 Slides)
Deliverables
Explain the various statistics used to express location and spread of data
Describe the characteristics of a normal distribution
Test for normality
Describe the difference between special cause and common cause variation
Generate a variety of graphs for data

Measurement System Analysis (62 Slides)
Deliverables
Perform the step by step methodology in variable and attribute MSA's
Identify the various components of variation so corrections can be made and the gage error reduced
Recognize the differences between repeatability, reproducibility, accuracy and calibration

Process Capability (36 Slides)
Deliverables
Estimate capability for continuous data
Describe the impact of non-normal data on the analysis presented in this module for continuous capability
Estimate capability for attribute data

Wrap Up & Action Items (10 Slides)

Analyze

Phase Description:
The Analyze section of the DMAIC methodology is constructed to introduce important Six Sigma tools for isolating critical factors. There are 9 modules in this phase.

Welcome to Analyze (4 Slides)

"X" Sifting (55 Slides)
Deliverables
Perform a multi-vari analysis
Interpret and a multi-vari graph
Identify when a multi-vari analysis is applicable
Interpret what skewed data looks like
Explain how data distributions become non-normal when they are really normal

Inferential Statistics (28 Slides)
Deliverables
Explain the meaning of the term "Inferential Statistics"
Describe the basic tenets of the Central Limit Theorem
Describe the impact of sample size on your estimates of population parameters
Explain standard error

Intro to Hypothesis Testing (28 Slides)
Deliverables
Articulate the purpose of Hypothesis Testing
Explain the concepts of the Central Tendency
Be familiar with the types of hypothesis tests

Hypothesis Testing Normal Data Part 1 (84 Slides)
Deliverables
Determine appropriate sample sizes for testing means
Conduct various hypothesis Tests for Means
Properly Analyze Results

Hypothesis Testing Normal Data Part 2 (56 Slides)
Deliverables
Be able to conduct Hypothesis Testing of Variances
Understand how to Analyze Hypothesis Testing Results

Hypothesis Testing Non Normal Data Part 1 (51 Slides)
Deliverables
Conduct Hypothesis Testing for equal variance
Conduct Hypothesis Testing for Medians
Analyze and interpret the results

Hypothesis Testing Non Normal Data Part 2 (36 Slides)
Deliverables
Calculate and explain test for proportions
Calculate and explain contingency tests

Wrap Up & Action Items (10 Slides)

Improve

Phase Description:
The Improve section of the DMAIC methodology is constructed to introduce important Six Sigma tools for process optimization. There are 8 modules in this phase.

Welcome to Improve (4 Slides)

Process Modeling: Regression (34 Slides)
Deliverables
Perform the steps in a correlation and a regression analysis
Explain when correlation and regression is appropriate

Advanced Process Modeling: MLR (51 Slides)
Deliverables
Perform Non-Linear Regression Analysis
Perform Multiple Linear Regression Analysis (MLR)
Examine Residuals Analysis and understand its effects

Designing Experiments (28 Slides)
Deliverables
Determine the reason for experimenting
Describe the difference between a physical model and a DOE model
Explain an OFAT experiment and its primary weakness
Shown main effects plots and interactions, determine which effects and interactions may be significant
Create a full factorial design

Experimental Methods (27 Slides)
Deliverables
Be able to Design, Conduct and Analyze an Experiment

Full Factorial Experiments (65 Slides)
Deliverables
Understand how to Create Balanced & Orthogonal Designs
Explain how Fit & Diagnose & Center points factor into an experiment

Fractional Factorial Experiments (37 Slides)
Deliverables
Explain why & how to use a Fractional Factorial Design
Create a proper fractional factorial design
Analyze a proper model with aliased interactions
Wrap Up & Action Items (10 Slides)

Control

Phase Description:
The Control section of the DMAIC methodology is constructed to introduce important Six Sigma tools for properly controlling solutions. There are 8 modules in this phase.

Welcome to Control (4 Slides)

Advanced Experiments (19 Slides)
Deliverables
Use the results of a DOE to determine how to further optimize a process using the steepest ascent/descent method

Advanced Capability (23 Slides)
Deliverables
Understand the importance of Capability Analysis as it is applied in the Control Phase
Select the appropriate method for Capability Analysis based on the type of data distribution of your process
Interpret the output of Minitab's Capability functions
Understand how the use for Capability Analysis may after through the DMAIC phases

Lean Controls (27 Slides)
Deliverables
Describe lean tools
Understand how these tools can help with project sustainability
Understand how the lean tools depends on each other
Understand how tools must document the defect prevention created in the control phase

Defect Controls (24 Slides)
Deliverables
Describe some methods of defect prevention
Understand how these techniques can help with project sustainability
Including reducing those outliers as seen in the advanced process capability section
If the vital X was identified, prevent the cause of defective Y
Understand what tools must document the defect prevention created in the control phase

Statistical Process Control - SPC (66 Slides)
Deliverables
Describe the elements of an SPC chart and the purposes of SPC
Understand how SPC ranks in defect prevention
Describe the 9 step route or methodology of implementing a chart
Design subgroups if needed for SPC usage
Determine the frequency of sampling
Understand the control chart selection methodology
Be familiar with control chart parameter calculations such as UCL, LCL, and the center line

Six Sigma Control Plans (40 Slides)
Deliverables
Understand the 5 phases of the Control Plan
Training
Documentation
Monitoring
Response
Aligning Systems and Structures

Wrap Up & Action Items (10 Slides)