Simple data analytics, better beer: Cheers!

In this Big Picture Interview, Deschutes discovers that you can get actionable info without analyzing every bit of data.

By Christine LaFave Grace, managing editor

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Tim Alexander is brewery operations technology manager at Deschutes Brewery in Bend, OR. After nabbing a couple of engineering degrees, he joined Deschutes as an intern in 2006 and never left. In 2014, Deschutes recognized that it was missing some of its fermentation points – acting too soon or too late in moving brews to the next step in the fermentation process – which can waste time and affect beer quality. The brewer turned to OSIsoft’s PI Integrator for Microsoft Azure to try to predict fermentation more precisely. Alexander shared with managing editor Christine LaFave Grace what the brewer has learned.

PS: In your presentation at the ARC Industry Forum in February, you said that one of the key lessons you’ve taken from Deschutes’ foray into data analytics is, “Don’t overcomplicate things.” Can you elaborate?

TA: When we first went into this, we were all really excited – OSIsoft, Microsoft, and us. Big Data, right? (It was) “We’re going to do something really cool here; we’re going to be able to model our fermentation perfectly.” So we started sending all of our temperatures for all of the tanks up into the cloud, all of the pressures on the tanks that we had pressure (monitoring) on, all of our outputs for temperature and pressure ... We thought, why not? Let’s just send it all up there. At one point it was going to be multivariate analysis on all of these things, (but) the Microsoft data scientists were starting to look at the data, and they said, OK, what are definitely the most important things (to look at)? We said, we think maybe the vessel could have an effect (on fermentation), and brand absolutely, because different brands ferment in different ways, and then we’re trying to predict a density curve, so the density measurement.

They started looking at everything, and they said: “The temperatures are relatively stable, because they’re being controlled, so there’s really no correlation with fermentation time and temperature. There might be a little correlation with the how open that microvalve is, but it’s really low. And even the vessel is not that big of an effect. You might be good enough just looking at the density and the brand.”

That’s what we did, and it ended up being this very simple model. We’re looking at literally one variable, and we’re contextualizing it with the PI Integrator, so we can group it by brand. (The data scientists) said, “Let’s start here, and then we can build if it’s not accurate enough.” We’ve been within a few percent, generally speaking, of our predictions, which is plenty of accuracy for what we’re trying to do.

It’s easier to make it work if you start simple. It’s daunting, right? “Oh, we have to look at all of that?” No. You can start as small as you want. You can look at one little process, one little piece of equipment. And maybe once you look at that, you find, “Oh, OK, it’s this really simple thing, and we can easily translate this to other processes.”

Hear from Tim in person at the 4th annual Smart Industry conference in Rosemont, IL, this September!

PS: What benefits  have you seen from data analytics in the cloud that you weren’t getting when you were manually plotting data in a spreadsheet and looking for trends?

TA: As the fermentation might change over time, now we’re able to adjust (for that). Also, you can get an early warning if something (isn’t) going right just by seeing that brand curve vs. your measurements and saying, “OK, this batch curve is not lining up.” Long before you can see it through the process of fermentation, you can see that, oh, yeah, this (batch curve) is not normal."

If something is going wrong with a fermentation, a lot of times it's something to do with the yeast not being happy. That might mean there's something in the wort, but that's extremely rare, and we would know if something had gone wrong. More typically it's like the yeast is having a bad day, or we didn't get the right amount of oxygen into the fermentation. Generally, oxygen helps yeast start (at the beginning of fermentation) so it can respirate instead of ferment. Typically once a beer is fermented, you would never add oxygen to it, because then it's going to start aging the beer. You can add oxygen at the beginning, but you don't want to add it as it gets late.

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