1. The Quality Improvement Model
Define Process
The Quality Improvement Model
Select Measures
Collect & Interpret Data
Collect & Interpret Data: Diagnosing Variability
Is Process Stable ? No
Investigate & Fix Special Causes
Purpose: Begin to understand why there is variability in data collected
Yes
Is Process Capable ? No
Improve Process Capability
Yes
Use SPC to Maintain Current Process

2. What size shoe do you wear?
Size 11 Shoes
Key word is WHY?
Manufacturing process varies
Different Manufacturers
Why aren’t size 11’s all the same size?

3. GC CHDM Test Method Example
Wish it was all the same % Water!
WHY isn’t it?
Will look at a tool to help us figure out WHY
Why don’t we get the same %Water value?

4. Cause & Effect Matrix – A Tool to Identify and Quantify Sources of Variation
Cause & Effects Matrix

5. Cause and Effects Matrix
Relates the key inputs to the key outputs (customer requirements) using the process map as the primary information source
Key outputs are scored as to importance to the customer
Key inputs are scored as to relationship to key outputs
Pareto of key inputs to evaluate in the FMEA and control plans
Input into the initial evaluation of the Process Control Plan

6. Cause & Effect Matrix Steps
Identify key customer requirements (outputs) from process map or other sources
Rank order and assign priority factor to each Output (usually on a 1 to 10 scale)
Identify all process steps and materials (inputs) from the Process Map
Evaluate correlation of each input to each output
low score: changes in the input variable (amount, quality, etc.) have small effect on output variable
high score: changes in the input variable can greatly affect the output variable
Cross multiply correlation values with priority factors and sum for each input

7. Examples
Note: Only a partial list

8. Bottle Production Example
Note: Only a partial Map

9. Cause & Effect Matrix Form
1. List Key Outputs
Excel Template C&E Matrix.XLS

10. Bottle Production Example
1. List Key Outputs
The Outputs are defined in Step 1 of Process Mapping

11. Cause & Effect Matrix Form
2. Rank Outputs as to Customer importance

12. Bottle Production Example
2. Rank Outputs as to Customer importance

13. Cause & Effect Matrix Form
3. List Key Inputs by Process Step
Note: Information obtained from process map

14. Bottle Production Example
This step uses the Process Map inputs directly. Notice the Process Inputs follow the Process map step-by-step.
3. List Key Inputs by Process Step
Note: Only a partial list of inputs

15. Cause & Effect Matrix Form
4. Relate Inputs to Outputs

16. Relating Inputs to Customer Requirements
You are ready to relate the customer requirements to the process input variables
Correlational scores: No more than 4 levels
0, 1, 3 and 9
Assignment of the scoring takes the most time
To avoid this, spell out the criteria for each score:
0 = No correlation
1 = The process input only remotely affects the customer requirement
3 = The process input has a moderate effect on the customer requirement
9 = The process input has a direct and strong effect on the customer requirement

17. Bottle Production Example
4. Relate Inputs to Outputs
Note: Only a partial list of inputs
This is a subjective estimate of how influential the key inputs are on the key outputs

18. Cause & Effect Matrix Form
5. Cross-multiply and prioritize
Sum of (Rating x Correlation Score) values for all Requirements

19. Bottle Production Example
5. Cross-multiply and prioritize
Note: Only a partial list of inputs
We now start getting a feel for which variables are most important to explaining variation in the outputs

20. Bottle Production Example
We have sorted on the cross-multiplied numbers and find that the input variables in the box above are the most important
We can now evaluate the control plans for these input variables
Note: Only a partial list of inputs

21. General Approach
Place the outputs across the top of the matrix and rank
Place inputs down the side of the matrix starting with the first process step and moving to the last
This approach is okay for small process with relatively few steps
Should only be used for processes with a relatively small number of steps and inputs

22. Focused Approach Phase I Phase II
Place the outputs across the top of the matrix and rank
Place the process steps down the side of the matrix
Correlate process step to outputs
Pareto the process steps
Phase II
Start a new C&E Matrix with the inputs from the top three or four process steps
Recommended when first starting a project
Focuses the efforts and gives the team a feeling that they’re working on the important process steps first
Gives you a running start at the FMEA and preliminary Control Plan Analysis

23. Control Plan Evaluation
Standard Operating Procedures
Do they exist?
Are they understood?
Are they being followed?
Are they current?
Is operator certification performed?
Is there a process audit schedule?

24. Control Plan Evaluation
Controllable Input Variables:
How are they monitored?
How often are they verified?
Are optimum target values and specifications known?
How much variation is there around the target value?
How consistent are they?
Other Questions:
How often is the input variable out of control?
Which input variables should have control charts?