nav[aria-label="Primary Navigation"] { padding: 0; & ul { list-style: none; width: 100%; display: flex; flex-direction: row; justify-content: start; align-items: start; gap: 30px; padding: 0; & li { margin: 0; } & ul li { list-style: none; } } }

747085_de-DE

liliconcom

How to automatically recognize the curvature difference?

I have the datalogs where tempeature readings are collected continuously as time goes by for each wafer. Temperature profile looks like a mountain.

I collected the temperature readings from 10 wafers and I want to compare the temperatura profiles together by illustrating the temperature readings along the same (relative) time axis. I want to check if some of them are normal or not. Some of the mountains are overlapped and some of them are not. Some have different peaks or starting points. Is there any way to differentiate between the shape difference (mountains) instead of differentiating them by naked eye visualization...? Thanks for any suggestions!

Data Exploration and Visualization

Re: How to automatically recognize the curvature difference?

Which JMP are you using (standard or pro) and which version? If you have JMP Pro check out Functional Data Explorer

Re: How to automatically recognize the curvature difference?

@Fruit325 - there are several ways to handle this... is there any way you can post an anonymized screenshot of a graph so we can help you determine the right one?

Re: How to automatically recognize the curvature difference?

Hi Mike,

Thanks! Here is an example:

We may differentiate the two curves from the peak.

Is there any way we could differentiate the two directly? Can we calculate the peak area? or locate the peak?

There are a lot of curves in our case and some of them may be overlapped or not, or have the same peak values.

Thank you!

Re: How to automatically recognize the curvature difference?

Unfortunately, I'm using JMP Pro.

Thank you so much, I will check the data explorer you shared.

Betreff: Wie erkennt man automatisch den Krümmungsunterschied?

Hallo, @Fruit325 !

Danke dafür. Sie haben mehrere Möglichkeiten, wie Sie damit umgehen können. Ich habe letztes Jahr tatsächlich eine Präsentation zu diesem Thema auf dem JMP Discovery Summit gehalten und es gibt eine Aufzeichnung. Sie finden sie hier: https://community.jmp.com/t5/Discovery-Summit-Americas-2023/Spectris-Spooky-Spectroscopy-2023-US-30MP-1472/ta-p/651680