A Digital Twin of my coffee roaster that runs in the browser
I built this website to host a data-driven model of my coffee sample roaster. I realized after 20 or so batches on the machine that while the controls are intuitive (heat, fan, and drum speeds), the physics can be unintuitive. I wanted to use my historical roast data to create and tune a model that I could use to do roast planning, control, and to help me build my own intuition for roasting. This website lets you interact with my roaster in a virtual, risk-free setting! The models are custom Machine Learning modules that honor roaster physics and bean physics (this is not…
In plain words
A Digital Twin of my coffee roaster is a browser-based simulator that models a sample coffee roaster using machine learning trained on real roast data. It lets users practice roasting virtually without risk by adjusting heat, fan, and drum speeds to understand how these controls affect the roasting process. The custom ML models incorporate roaster and bean physics rather than using general-purpose AI. Designed for coffee enthusiasts and roasters seeking to improve their technique through experimentation and intuition-building in a safe, risk-free environment.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
I built this website to host a data-driven model of my coffee sample roaster. I realized after 20 or so batches on the machine that while the controls are intuitive (heat, fan, and drum speeds), the physics can be unintuitive. I wanted to use my historical roast data to create and tune a model that I could use to do roast planning, control, and to help me build my own intuition for roasting. This website lets you interact with my roaster in a virtual, risk-free setting! The models are custom Machine Learning modules that honor roaster physics and bean physics (this is not GPT/transformer-based). Buncha math. The models are trained on about a dozen real roasts. The default bean model is an Ethiopian Guji bean. My next steps are to add other roasters and the ability to practice control/reference tracking.
Does the same job
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