Multi-vari charts help you to identify sources of variation. Use these charts to see within piece, piece to piece, and time to time variations.
Multi-vari vs other chart types
Recap of variation sources
- Within piece: variations within a single instance of a product. Also known as positional variation.
- Piece to piece: variations that occur between different instances of the same product. Also known as cyclical variation.
- Time to time: variations that occur at different production times. Also known as temporal variation.
Generate Clues with Multi-vari Charts. This technique is especially well suited for analyzing multiple sources of common-cause variation: within piece, piece to piece, time to time, and process stream to process stream.Reducing Process Variation- Davis Bothe
Benefits of Using Multi-Vari Charts
A multi-vari chart can:
- Show most of your variations.
- Assist you in breaking down the components of variation.
- Show all measurements recorded.
Guidelines for Creating Multi-Vari Charts
When creating multi-vari charts, keep these points in mind:
- Numeric data: You need to be able to plot the effects of variations using mean values.
- Factors: Use a maximum of six factors.
- Levels: You need at least two levels for each factor.
- Amount of data: Collect observations for the majority of factor combinations.
Creating a Multi-Vari Chart
- Time is on the horizontal (x) scale.
- Variable measurement is on the vertical (y) scale.
Let’s walk through creating a multi-vari chart using a basic baking problem.
I’m baking cookies using three different ovens. Some of my cookies seem a bit wider than others. I need to figure out why. They’re all made from the same ingredients and recipe. So I think the most likely factors are:
- Placement on the cookie sheet. (within piece, treating each sheet of cookies as a ‘piece’)
- Temperature variations between ovens. (piece to piece)
- Temperature levels in the kitchen when the cookies are being mixed and added to sheets. (time to time)
Therefore, I’ll use these three factors in my chart.
Firstly, I need to take width measurements on every cookie. I also need to record:
- The oven it was baked in.
- The batch it was part of.
- Its location on the cookie sheet.
So I fill out this data table:
|Oven 1||1||Left middle||4.11|
|Oven 1||1||Right middle||4.1|
|Oven 1||2||Left middle||4.11|
|Oven 1||2||Right middle||4.09|
|Oven 1||3||Left middle||4.12|
|Oven 1||3||Right middle||4.09|
|Oven 1||4||Left middle||4.11|
|Oven 1||4||Right middle||4.09|
|Oven 2||1||Left middle||4.11|
|Oven 2||1||Right middle||4.11|
|Oven 2||2||Left middle||4.12|
|Oven 2||2||Right middle||4.12|
|Oven 2||3||Left middle||4.12|
|Oven 2||3||Right middle||4.13|
|Oven 2||4||Left middle||4.11|
|Oven 2||4||Right middle||4.09|
|Oven 3||1||Left middle||4.11|
|Oven 3||1||Right middle||4.1|
|Oven 3||2||Left middle||4.11|
|Oven 3||2||Right middle||4.09|
|Oven 3||3||Left middle||4.12|
|Oven 3||3||Right middle||4.1|
|Oven 3||4||Left middle||4.11|
|Oven 3||4||Right middle||4.09|
To turn the data table into a chart, I use Minitab.
I copy and paste my table into its spreadsheet. I then select Stat > Quality Tools > Multi-Vari Chart from the menu.
I tell Minitab which column contains my results (Response). Then I select my variables (Factors 1 to 3).
I click on OK.
Minitab creates the chart for me.
Interpreting the Results
One thing immediately jumps out at me when I look at this chart: the center measurements are perfect. In every other oven location, though – back, front, left middle and right middle – the measurements for Oven 2 are substantially skewed from Oven 1 and 3.
I can probably remove a lot of variation by servicing or repairing Oven 2.
Additional Helpful Multi-Vari Videos
Complimentary information to Multi-Vari Study, Multi-Vari Charts
Find further information and examples in this PDF: Multi-Vari Analysis.
Six Sigma Green Belt Certification Multi-Vari Study, Multi-Vari Charts Questions:
Question: In an “X” Sifting exercises a Belt will use a(n) _______________ to assist in isolating families of variation that may exist within a subgroup, between subgroups or vary over time.
(A) Multi – Vari Chart
(B) Pareto Chart
(D) Shewhart Analysis
Six Sigma Black Belt Certification Multi-Vari Study, Multi-Vari Charts Questions:
Question: Positional, cyclical, and temporal variations are most commonly analyzed in: Taken from (ASQ sample Black Belt exam.)
Answer: (B) Multi-vari charts. SPC or statistical process control (including run charts) help you monitor how an on-going process is performing, so options A and D are not correct. Cause and effect diagrams are concerned with root cause analysis, so option C is not correct[/membership]