Robert Butler

Ok, that answers one of my questions. I still need to know what constitutes a rigorous design. Given your answer to the question of order I’m guessing all rigorous means is that you actually take the time to implement the design and not stop at some point and shift over to a WGP analysis (wonder-guess-putter), however, I would still like to know…[Read more]

You will have to provide a little more detail before anyone can offer much.
1. What is a rigorous experimental design?
2. What are lower and higher orders?

Give two levels for each factor you have the following:
Factor A, df = (a-1)
Factor B, df = (b-1)
Factor C, df = (c-1)
Factor D, df = (d-1)

in each case a = b = c = d = 2

For each interaction
AxB, df = (a-1)*(b-1)
AxC, df = (a-1)*(c-1)
etc.
AxBxC, df = (a-1)*(b-1)*(c-1)
etc.
and
AxBxCxD = (a-1)*(b-1)*(c-1)*(d-1)
Error, df = a*b*c*d*(n-1) where…[Read more]

1. Control charts do not require normal data – see page 65 Understanding Statistical Process Control 2nd Edition – Wheeler and Chambers
2. When you have the kind of count data you have it can be treated as continuous data – see page 3 Categorical Data Analysis 2nd Edition – Agresti
3. I-MR would be the chart of choice – you should check to make…[Read more]

DOE is a method for gathering data. Regression (any kind of regression) is a way to analyze that data. As a result it is not a matter of using DOE or regression.

Experimental designs often have ordinal or yes/no variables as part of the X matrix. The main issue with a design is that you need to be able to control the variable levels in the…[Read more]

I would like to offer a few comments and make a few recommendations with respect to your initial post.

Statistical methods, machine learning, advanced methods of data analytics and statistics are all tools one can/does use in the analysis phase of six sigma. In this light, the observation “Of course, these techniques would be used after the…[Read more]

@cseider I suppose it could be but if it is I would nominate the question for the scatological award for worst posed homework question of the year.

As asked your question has no answer because you have not provided any information about your production line. For example, if the process target is 1 ppm and my in control process 3 standard deviation limits around that target are plus/minus .01 ppm the answer would be – not a thing.

The standard calculation for Cpk requires normality in the data. Your data is naturally non-normal so what you need to do is use the methods for calculating Cpk for non-normal data. Chapter 8 of Bothe’s book Measuring Process Capability has the details of how to do this.

The basic method consists of plotting the data on normal probability…[Read more]

As I said in my first post – the problem is that of sample independence. If your batches consist of something like widgets stamped out on a production line then you would need to first take as many samples as you can at a uniform time interval for a single batch and run a time series analysis to determine the minimum separation in time between…[Read more]

Ok, sounds good.

So, is it a total of 30 samples from 6 batches for a total of 5 samples per batch or is it a case of 30 samples from each of 6 batches for a total of 180 samples?

To your points
– It’s not that I don’t recommend trying more than three rather it is the odds of finding raw material lots (a minimum of 6 if we go with the D-optimal design I mentioned earlier) with the right levels for each of the 6 combinations. If you have prior data on lots of raw materials it would still be worth examining the data to see…[Read more]

I’m a statistician – discussions like this are never a bother. :-) As to your plan – there is a problem with the way you have laid out the supplier information – specifically it does not match the example you provided earlier and which I used as a starting point for my post yesterday.

In the earlier post you gave the following:

supplier 1…[Read more]

Addendum to the last post: One thing to keep in mind when your low’s and high’s have ranges of values is the “fuzziness” of the -1 and 1 settings can be an issue. If the highest low value and the lowest high value for a given variable are too close together you may find you will lose information with respect to some variable interactions. In…[Read more]

Ok, let’s make that assumption. You have the following:

supplier 1 670 Rm and 19% elongation
supplier 2 640 Rm and 15% elongation
supplier 3 650 Rm and 19% elongation

Therefore what you have are the following combinations for the two factors Rm and elongation
Supplier 1 +1 and +1
Supplier 2 -1 and -1
Supplier 3 -1 and +1

The key here is…[Read more]

Since each of the supplier lots are allowed to vary within a range of (separate?) values for tensile strength, elongation, and roughness and since you only want to run an analysis where you are controlling your in house process parameters the best thing to do would be to review your collection of spec sheets from prior lots of raw material and…[Read more]

I think we need to back up a bit. If I understand your most recent post correctly you get a spec sheet from a supplier which provides tensile strength, elongation, and roughness measurements on each shipped lot. If this is the case then this would argue that you have zero control with respect to independently varying these three measures – for…[Read more]

Since you are concerned with the ranges of incoming material properties in addition to the things you vary in your process a better approach would be to run a saturated design on the 8 variables

Tensile Strength: from 600 to 800 N/mm^2
Elongation: from 20% to 10%
Roughness: from 2 to 0,5 µm
Energy Flow (Ampere)
Upsetting speed…[Read more]

You will have to provide more detail before anyone can offer much in the way of advice.
Questions:
1. What kinds of questions are on the survey? Are they yes/no, or are they Likert scale (ratings 1-5, 1-10), or are they multiple choice or are they open ended please-add-a-comment kind or is the questionnaire a combination of all of the…[Read more]