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Aug 25, 2016 6:17 PM
(880 views)

Hi- I made 9 different chemical formulations using 6 ingredients (adding different wt% of each). I make a certain amount (g) of byproduct for each of the 9 formulations, the amount dependent upon how we formulate (ratios added). What would be the best way to analyze and make sense of the data? Ideally want to determine the best formulation to give the minimum amount of byproduct. I appreciate the help.

Tade

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Solution

Tade,

If you double-click your column what does your column information look like? I am curious to first ensure that you have the columns coded correctly. It should resemble this...

If it does resemble this then perhaps you do not have enough degrees of freedom to fit a Scheffe cubic. Have you just tried a main effects and two-way interactions (non-linear blends) model?

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Aug 25, 2016 11:44 PM
(586 views)

I would recommend to:

1. Visualize your data, e.g. using the graph builder. Use graphs to give you an idea in which direction the data leads you. Check for potential outliers as well.

2. Then try to find an adequate model in the "Fit Model"-plattform. Make sure to set all factors in the model to mixture using the little red triangle next to "Attributes" in the fit model plattform. The JMP help gives an intro to the analysis of mixture experiments: A Chemical Mixture Example

Overall you might want to read about Design of Experiments for Formulations (Mixture Designs) for future studies if you are not already aware of that topic.

Hope that helps,

Sebastian

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Aug 26, 2016 5:16 AM
(586 views)

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Aug 31, 2016 11:40 AM
(586 views)

Sebastian, Lou,

Thank you. I ended up using Scheffe polynomial in Mixture design. However, the Prediction Profile I am getting looks more like blank like this:

What am I missing? Thanks for your help.

Tade

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Aug 31, 2016 12:19 PM
(586 views)

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Tade,

If you double-click your column what does your column information look like? I am curious to first ensure that you have the columns coded correctly. It should resemble this...

If it does resemble this then perhaps you do not have enough degrees of freedom to fit a Scheffe cubic. Have you just tried a main effects and two-way interactions (non-linear blends) model?

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Aug 31, 2016 1:46 PM
(586 views)

Thank you both for quick responses.

I tried changing the Y scale on the Prediction Profiler but didn't work. Here is my column information look like.

For the model, I selected Scheffe Cubic and it listed all the interactions. I have five factors and nine different combinations.

Thanks.

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Aug 31, 2016 2:42 PM
(586 views)

I checked L PseudoComponent Coding for each column for factors.

I

But I am getting the same results. No Y values no profile lines in the Prediction Profiler. Thanks for the help.

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Aug 31, 2016 7:44 PM
(586 views)

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Sep 1, 2016 2:52 PM
(586 views)

Tade,

If you are using a Scheffe cubic with 5 mixture factors with 9 unique formulations then you have an over parameterized model, ie not enough df to estimate all terms. If you would be willing to sanitize your JMP dataset and share then I think the guidance you could receive may help you get to a solution faster. Also I am assuming those 9 runs did come from a properly designed mixture experiment which was generated to support a particular model. If that is not the case, then estimability of any particular arbitrary mixture model may or may not be possible depending on how those 9 points cover the mixture space. You have already received some great input from Lou and DanO so please do consider their feedback.