What is process variation in Six Sigma?

What is process variation in Six Sigma?

Variation in Six Sigma is any result that is not what the customer expects, even if it is just not when the customer has expected it.

What are the major categories of variation in multi-vari studies?

To determine which category of input variable drives the performance of your process output, all you have to do is graphically decide which of the three types of variation — positional, cyclical, or temporal — displays the greatest magnitude of variation in your multi-vari chart.

What multi-vari chart indicates?

The multi-vari chart indicates a possible interaction between the machine and the temperature settings.

What does multi-vari analysis study?

Multi-vari charts are used to investigate the stability or consistency of a process. The chart consists of a series of vertical lines, or other appropriate schematics, along a time scale. The length of each line or schematic shape represents the range of values found in each sample set.

What are the main variations of Six Sigma?

Two types of variation concern a Six Sigma team:

• Common cause variation – All processes have common cause variation. This variation, also known as noise, is a normal part of any process.
• Special cause variation – This variation is not normal to the process. It is the result of exceptions in the process environment.

What is positional variation?

Positional variation is also known as “within part” variation. In manufacturing processes it would normally be the variation across a part (eg surface finish) or the variation across a unit containing many parts or by position in a batch process.

What are some potential pitfalls with a multi VARI study?

The following are a list of potential pitfalls using multi-vari studies: Confounding of input is present or multicollinearity. A DOE should be performed to further examine the interactions of the inputs. Interactions may exist within the data but are not shown with studying one “x” at a time.

What is the principal advantage of multi vari charting?

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.

What are the different types of causes for variation?

Common-cause variation is the natural or expected variation in a process. Special-cause variation is unexpected variation that results from unusual occurrences. It is important to identify and try to eliminate special-cause variation.

How do you identify variations in a process?

Use run charts to look for common cause variation.

1. Mark your median measurement.
2. Chart the measurements from your process over time.
3. Identify runs. These are consecutive data points that don’t cross the median marked earlier. They show common cause variation.

What are the 5 types of variations?

Examples of types of variation include direct, inverse, joint, and combined variation.

How to reduce variation with Six Sigma study guide?

DMAIC methodology is the Six Sigma standard on how to identify variation in a process, analyze the root cause, prioritize the most advantageous way to remove a given variation, and test the fix. The tools you would use depend on the kind of variation and the situation.

Why do you need data for six sigma?

This data is required to understand the measurement system variation (done via MSA) and the process variation. Once the MSA is concluded (and hopefully passed) the remaining variation is due to the process. The Six Sigma team should focus on reducing and controlling the process variation.

How are sample families of variation broken down?

A sample Families of Variation (FOV) diagram is shown below. The entire amount of variation found in a set of data can be broken down to the variation from the Process + the variation from the Measurement System, which should be calculated from the MSA. An FOV diagram starts drilling into the sources of Process Variation.

How many sources of variation are there in multi vari?

The remaining variation of the total is related to the PROCESS. Within the process, the team found came up with 5 sources of variation to examine. The GB/BB then ran Multi-Vari charts with ANOVA tests on four of the sources and used F-test and 2 sample t-test on another source.