A 'digital twin' is a model that evolves over the lifetime of a physical asset. So if the state of the real device changes, so does the model (data assimilation). Likewise, one can use the model for control/planning/"what-if" scenarios. This is the bi-directional information flow that's being mentioned.
So what I'm showing on the website is just the model part. I'm not a fan of exposing my hardware in a public demo (the digital twin part), but the idea is that this model evolves with the roaster during the roast (data assimilation) and can help the operator guide the roaster to a desired end goal (e.g. medium roast along some profile or with minimal energy usage).
Yeah, as shown it's just a bunch of models. The real magic happens when this is connected to hardware and we can do things like data assimilation and control.
100% agree - each roaster is slightly different, with different measurement schemes and other device peculiarities. This makes sharing coffee roasting profiles basically impossible!
I'm also working on letting people upload their roast profiles for training and serving their own models (including a "library" of bean models!).
Working on it! In fact, this was my original goal; Model Predictive Control for my roasters. I've been able to get this working on a fluid bed roaster but I've yet to try it for my drum roaster. Stay tuned! I'm hoping to have a control demo posted on the site soon.
So what I'm showing on the website is just the model part. I'm not a fan of exposing my hardware in a public demo (the digital twin part), but the idea is that this model evolves with the roaster during the roast (data assimilation) and can help the operator guide the roaster to a desired end goal (e.g. medium roast along some profile or with minimal energy usage).