Mixture DOE

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    I have been tasked with performing a Mixture DOE & i could do with some advice. I’m familar with factorial DOE’s but not mixtures. I’ve done some research in the types of MDOE-simplex centroid, lattice, extreme vertices, but im still unsure about the approach.

    The experiment would be based on a mix that is coated on to paper to enable a good print quality. I have 5 critical X’s ( 3 binders & 2 pigments). For a typical 1000 kg mix Pigment A is 600 kg, pigment B 350 kG, Binder A 20Kg, Binder B 20Kg & binder C10 Kg. This is just an example of 1 mix, other mixes have varying proportions of the different components.

    The critical Y’s im looking at are smothness, pick, gloss & whiteness of the coating. I’m trying to rationalise the number of mixes produced, possibly reduce costs on the expensive pigments & create predictive models for my critical Y’s.

    I’m using Minitab & have experimented with some extreme vertices designs. Could anyone give some advice on this matter.





    I am not an expert in extreme vertices designs, but I did a lot with fractional factorial DOEs in injection plastics (resin, colorant, heat, time, etc.). I think there may be advantages there especially if you skip run randomization and script a sequence to minimize change-overs and materials… Let me know if you want to discuss it further…

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