Hello all. I'm new to JMP and have been reviewing many of the use cases and webinars. I'm looking for a strategy on how I can approach optimizing the process conditions of a batch manufacturing process. There are plenty of resources about the multivariate analysis I would like to do, but I haven't found how to approach my goal because of the nature of the process. I have two data sources I'm dealing with: The first is a spreadsheet with continuous process data (temperature, pressure, etc) that is grouped Batch IDs. They are hourly averages. For example, if I'm looking at Batch ID #305, it might take 12 hours to fully process, so there is continuous information recorded in the spreadsheet. The second spreadsheet is the quality results of the batch after it has been completed. It is a single sample that is taken at the end of the batch. Continuing with the example I stated from the first spreadsheet, this spreadsheet would have a single row that would say Batch ID #305 and the strength of the batch that was determined from the quality lab. I have seen videos of multivariate methods to study the effect of one continuous process condition on another (temperature vs. pressure), but I'm not sure how to set up my data so that I can profile a process condition and study its effect on the final quality. The quality (or response) data is not continuous, but it can be tied to the continuous data because the Batch IDs exist on both spreadsheets. Any ideas on how to approach this? Thanks!
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