How does the Brew Data system help you make better beer? Lets look at a case study.
Here is glass a of finished beer:
Its an english bitter. Its a good beer, but it has a few fault. The yeast hasn't cleared very well and it has some slight sulphery notes. These are prime indicators that something isn't quite right in the fermentation. One of the first things to check is the fermentation temperature. Here is the actual temperature inside the fermentor for this batch:
On 1/14 the brewer filled the fermentor and the yeast started working. For about 3 days the yeast generated enough heat for the temperature to be close to setpoint and the glycol cooling turned on a few times. After the most vigorous phase of fermentation subsided, the temperature started to drop. After about a week, the temperature was almost 50F, too cold for the yeast to do much. The gravity dropped during the main fermentation, but after the temperature became too cold, the gravity stopped dropping, giving the illusion that the fermentation was finished. On 1/22 the brewer changed the setpoint for a cold rest but this failed to clear the beer as the fermentation was never finished.
Since the glycol system can only cool, most breweries rely on the self heating effect of the yeast and ambient temperature to keep things warm enough. Lets take a look at the ambient temperature plotted against the setpoint and fermentor temperature:
By looking at the ambient temperature compared to the setpoint, its becomes obvious the the problem with this batch of beer is that the ambient temperature was too low. Further investigation showed that the room heater was actually turned off for part of the fermentation and then was set too low.
A quick check of the ambient temperature proves that this problem has been fixed:
This case study demonstrates how the Maxidaq data acquisition and control system can help you make better beer.