# Multi-Vari Help on Experiment Results

S

#### Stuart_W

Hi

Am hoping for some guidance please for my six sigma project.

I have a process whereby machined steel bars are transported from Hungary to the uk (warehouse) and then subsequently brought in house here in the UK for further processing. These bars have a cast iron hub shrunk on the ends and they are transported vertically in individual VCI bags.

So I have done a number of controlled deliveries where we have ensured that the correct process has been followed and local conditions were recorded.

My Y is rust on shaft end (On the iron hub) and I have basically 2 levels (No rust or rust).

Xs include: Type of top support (foam, nylon)
Bag condition at top (Good, hole (small), hole (large), split
Bag condition at bottom (As above)

Now because my y is not continous, I'm basically saying the shaft end is rusty or it's not I've confused myself because it seems Minitab wants to see a Y with a continuos output.

I would appreciate any advice as to hw to proceed to establish which of my factors (if any) influences wheter or not the iron end is rusty.

TIA

Stuart

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#### NumberCruncher

Re: Multi-Vari help on exeperiment results

Hi Stuart

Your x data are also not continuous but categorical.

I have only just aquired a copy of Minitab, so I can't help you there. However, you may be able to use rank correlation if the degree of rust is noticeably different on the shafts.

Let's say that you have 10 shafts. Order the shafts with the least rusty at one end, working through to the most rusty at the other. Then rank them from 1 to 10. If you decide that two shafts are about as rusty as each other, give them the same rank.

For example, shaft numbers 4 & 5 are about the same, your ranks will be 1,2,3,4,4,5,...9.

The Kruskal-Wallis test is a non parametric version of ANOVA. If you have enough data you should be able to get Minitab to do the analysis.

NC

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