Details of the method used are at...

Optimizing Factor Levels when Results are Qualitative]]>

I conducted a full factorial experiment with three factors à 2 levels each. I did not conduct replicates of those but added 3 center points.

Factors:

o Incubation time (0h, 2h, 4h)

o Process temperature (30°C, 40°C, 50°C)

o Process duration (Time) (4h, 7h, 10h).

Ouput variables: texture coefficient, yield.

Here’s my data:

Nr. Text. Yield Incub Temp Time

1 h1 2.63 54 0 30 4

2 h2 1.71 51 4 30 4

3 h3 2.37 56 0 50 4

4 h4...

Analysis 2^3 with 3 center points]]>

I was running an unreplicated two-level factorial design with three center points for screening of my factors.

The ANOVA-output of my data gave me a significant regression (which is good), but also a significant curvature together with an insignificant lack of fit.

My interpretation of this is that i do have a significant curvature, but my regression model is nonetheless able to model my datapoints (the residual plots also look as if the regression does adequatly model...

Significant curvature with insignificant LoF]]>

What would be the best approach for an only experiment with 4 factors?

Acid

Temperature

Concentration

Time

The thing is that there are two important considerations in this experiment and its necesary some ideas to apporach the experiment correctly.

1. There are three different acids and they wouldnt combine ever.

2. One of them (Acid C) allows a higher temperature due to its boiling temperature.

It looks something like this:

Acid A

Temperature: 10-20 ºC

Concentration: 5-10 %...

Designing an experiment with some consideretions]]>

So my question is, numerically speaking, are the edge of limits of the DoE the tolerance values of the QTPP and CQA parameters?

Thanks in advance.]]>

after my ANOVA the R² of the model is really bad (R² = 0,1743) and it has a significant lack of fit (lack of fit = 0,0096). I used 8 factors but only one was selected as significant.

1.) The lack of fit tells me, that the model needs to be extended by another term (quadratic term, 2-way-interaction or a completely new term). Is that right?

2.) One factor was identified as highly significant (p = 0,012). Is it ok to trust this result, although the model (lack of fit, R²)...

Can factors be significant if there is a lack of fit and weak R²?]]>

I have a question whether significance (high p-value) and effect size are proportional?

I did already read that highly significant results do not necessarily need to have a big (practical) effect on my response.

Definition from Wikipedia: Statistical Significance:

Main article: Effect size

Effect size is a measure of a...

The higher the significance the higher the effect size?]]>

My colleague did a design with 4 factors and 8 runs and said its a Plackett-Burman Design with resolution III.

A picture of his design is attached.

I read a little bit about DoE now and in my opinion its a resolution IV design and I would call it rather a Fractional Factorial Design than a Plackett Burman design. Am I right or is he right?

Thanks,

Marcel]]>

I am new in DOE tecnique and this is the reason why I am asking you help.

I must provide a DOE tecnique in order to obtain an analytical correlation... in particular, I have 3 factors (A,B,C) and 3 level for each one.

A 0.59 0.69 0.77

B 16.2 24.2 32.2

C 3.2 3.4 3.6

I am using the book "Design and Analysis Experiments" by Douglas C. Montgomery; I read that "the 3^k design is not the most efficient way to model a quadratic relationship" and...

First time approching DOE tecnique - help -]]>

I would like to obtain response surface for a problem driven by 4 variables. Hence I defined 5 levels for each variables (-alpha;-1;0;+1;+alpha), and used a CCD approach.

However, the extremum of one variables(+alpha and -alpha) seem to degrade the results.

I am fairly new to designs of experiment, and I would like to know the implications of only having 3 levels for 1 variable while having 5 levels for the others. Is the...

Central Composite Design (CCD)]]>

CCF Design Axial Points Outliers]]>

Single Replicate DOE Help]]>

I am trying to find out which process parameter / parameters (temperature, time, pressure etc.) have the effect on process response.But i do not mean DOE.

There is a process which is not really stable. All the parameters are already set and use in the same way, but due to several factors is their performance being changed according to material purity, machine condition etc.

Do i need to use a Regression analysis?

I thought that, but today i found, that by Regression...

Relationship between a response and predictor variables]]>

I have a problem with my DOE in Statistica software. I have 3 dependent variables, and one independent.

I have 8 runs, just like on this photo:

https://postimg.org/image/g01rw6avn/

And my model has 3-way interaction. But, when i select 3-way interaction i can't get standard error and p of every coefficient. But, when i select 2-way interaction, i get everything and that's ok:

https://postimg.org/image/t38x0qcdr/

But, i can't see this for 3-way...

2^3 DOE Problem]]>

Do factors need to be Independent of each other in an experimental design? Let's say Independent factors in my experiment are X,Y,Z

So if I'm designing an experiment, Is it appropriate to take these 3 factors if it is known that a change in X results in change in Y or Z?

Looking forward to your answer..

Thank you.]]>

i would like to improve the polishing quality of opthalmic lenses and use a DOE for it.

The opthalmic lenses are being polished and at the end of a process needs to be checked the following:

1. by sight, if the surface is polished well (no markings from previous smoothing operation)

2. by sight, surface shall not content scratches, pits or dots

3. surface can not be polished too much, because of power of a lens (the more is a lens polished, the more deviation could be occured)...

DOE to improve polishing quality of ophthalmic lenses: No variable response]]>