How to compare the results between two DoE/Response Surfaces?

Question

Hey,

I have been characterizing different reactors using DoE to establish the correlation/equation between identical one response y and two independent parameters x1, x2. The DoE and data analysis for each reactor were not designed with JMP but in Python.

Now, I would like to get the correlation on one reactor and compare statistically the correlation with other, assessing differences and similarities..., with JMP. I though on overlapping the surfaces plots, for instance, but would like to explore JMP capabilities. The Python generated the tables for each reactor on x1, x2 & y. I couldn´t find any tutorial to develop such a comparison given that the DoE wasn´t initially designed in JMP. I have the results directly.

How could I input the data into JMP and perform the comparison?

Thank you

statman · Answer

I'm a bit confused...why don't you use "your" software to do the comparison. ("Since the design of the DoE and the response values calculation was done outside JMP, I would like to use your software to do the final step of comparing the results.").  If you add the data table, it is much easier to provide advice.

Also, this can't be correct: "Regarding your questions, R1 from Site A and the R2 from Site B (same volume, temperature) where analyzed on the same design space".  No way they could be the same!  Different raw materials, ambient conditions set-ups, sensors, measurement systems, etc.  I also have run a number of experiments across multiple reactors.  Reactor is not a factor, but likely confounded with block.  Analyze at the block averages. You can add block to the model (and block by factor interactions).  I have often found factor effects (X1 & X2 in your case) dependent on reactor (a block by factor interaction).

P_Bartell · Answer

Lots of options and workflows within JMP for this type problem and data. You've told me nothing so far that leads away from doing what I recommend in my second to last paragraph in my initial reply. This will allow you to gain insight with respect to your practical questions BEFORE any modeling work to create response surfaces. At a minimum I suggest exploring these 5 issues:

1. Where's the middle of the responses for each 'x'?

2. What's the shape of the responses for each 'x'?

3. How spread out are the responses for each 'x'?

4. Plot the responses in order of experimental execution.

5. Are there any response data that look suspicious, odd, unexpected, or unusual that might make subsequent modeling more problematic? If so, how will you handle them in subsequent analysis and reporting?

A simple run chart (for issue #4 and the Fit Y by X platform for the rest are your friends here. Graph Builder could work too.

Once you get to modeling, and I presume you have 'useful' models, the JMP Prediction and Contour Profilers will be invaluable for additional response surface visualization and comparison.

Upa_Upitas · Answer

Hey Bartell,

Thank you for answering. I agree on keeping the comparison simple. Maybe to start, I would like to learn how to overlap response surfaces between Reactor 1 (R1) and Reactor 2 (R2) to visualize and asses the response space upon x1 and x2. Maybe next to perform a t-student analysis to asses the difference between y in R1 to R2.

Regarding your questions, R1 from Site A and the R2 from Site B (same volume, temperature) where analyzed on the same design space using a DoE methodology. x1 and x2 are in similar ranges. Obviously, since the experimentation was done in two different factories, there are many things not completely identical. There are central runs. Each characterization has 6 to 9 runs.

Since the design of the DoE and the response values calculation was done outside JMP, I would like to use your software to do the final step of comparing the results.

My purpose is to assess the differences in the response  between Site A and B.

Thank you for any input in this matter :)