Process optimization using JMP

This short video shows how to use JMP to design the experiments, create multiple regression (surrogate) models quickly, evaluate and deploy them inside JMP, then use the models to optimize the process.
To note, I jump :) to using my usual method of not following the "Easy DOE" feature of JMP when building the model, as it is a new feature in JMP. But, the workflow is the same.

HYSYS is used as the "plant" or the digital twin of the plant along with its excellent cost estimation feature to make a very quick analysis.

If you're wondering how to improve the models' performance, you have to run the experiments set by JMP religiously. In this example, I only ran 10 experiments. Hence, the accuracy in the optimization step is not really good. Nonetheless, the steps mentioned in this video remain valid.

#JMP, #HYSYS, #chemicalengineering, #designofexperiments, #DOE, #regressionmodels, #processsimulation, #statistics