Welcome to process-improve Discussions!

[kgdunn]

👋 Welcome to process-improve Discussions

This is the place to talk about multivariate analysis, designed experiments, process monitoring, and everything else that lives in or around process-improve. Whether you're building a calibration model for NIR spectra, monitoring a fermentation, designing a screening experiment, or working through a chapter of Process Improvement using Data — you're in the right place.

What Discussions are for

Use Discussions for anything open-ended:

• Q&A — "Which method should I use for this data?", "Why is my PLS model giving these scores?", "How do I align batches of unequal length?"
• Show and tell — share a use case (anonymised is welcome), a plot you built, or an analysis you're proud of. Industrial chemometrics work is usually hidden behind NDAs; this is a rare chance to see how others actually apply these tools.
• Ideas — features you'd like to see, methods worth adding, parts of the API that feel awkward, papers worth implementing.
• Announcements — new releases and significant additions will be posted here.

Issues are reserved for confirmed bugs and tracked development work. Everything else belongs here.

A few starter prompts

If you're not sure where to begin, any of these makes a great first post:

• Introduce yourself — what industry, what kind of data, which method you reach for most often.
• A question you've been stuck on — even if it's not strictly about this package, the community probably has useful angles on it.
• One thing you wish chemometrics tooling did better.

About this community

process-improve started as a companion to the textbook Process Improvement using Data and is now used by practitioners across pharma, food, chemicals, and discrete manufacturing, alongside students and researchers. The methods here are deep, the literature is scattered, and almost everyone — myself included — has had to learn this material the hard way. Questions at every level are welcome.

To get started: drop an introduction below — who you are, what you work on, and what brought you to the package.