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and then finding out if their concept will make the grade and be commercial someday.”

Sharing Knowledge

While Tiffany has, for over 25 years, been a university-employed production economist working outside of the biofuels sector on the boundary of academia and industry, he appreciates the people he’s met and worked with in ethanol. “I’ve really enjoyed visiting with the folks at the plants, going back to the days when I would visit frequently with the people over at Chippewa Valley Ethanol Co. in Benson, Minnesota,” he says. “Kelly Davis, Andy Zurn, Bill Lee—they were all very patient helping me understand the ethanol process so I could do my work. Sometimes it was just a couple quick questions—maybe five minutes—but it meant a lot to me.”

Tiffany says the things that impress him most about the ethanol industry, and pull him to it often, are “the great people” and “the pace of innovation.” He says that nowhere is that more noticeable than at the annual International Fuel Ethanol Workshop & Expo. “Just amazing, the number of new things you would see for the first time at that show— whether it was corn oil extraction or corn fiber-to-ethanol technology,” he says. “Things have happened very fast in ethanol, and it’s been exciting to watch.”

Like millions of Americans, Tiffany is currently working from home. “We all just need to stay safe right now, so we’re finding new ways to innovate, communicate and make things happen,” he says. “It can be a little isolating at times—not being able to bump into a colleague in the hallway and ask them a question—but that’s our reality for a while.”

University employees aren’t traveling during the pandemic, but Tiffany says he is thankful for the many rewarding opportunities he has had over the years to travel internationally, present at conferences, participate on boards and testify in front of government committees. For example, he has provided expert testimony to Minnesota state legislative committees on first- and second-generation biofuels; and he served as a governor appointee on Minnesota's Nextgen Board, which provided recommendations and grant funding aimed at energy independence and sustainable natural resource utilization.

Tiffany is not part of the U of M’s teaching faculty, but rather its research faculty—an important distinction—but opportunities to lecture and present, nonetheless, give him joy. Many years ago, he had an opportunity to speak to cadets at the U.S. Military Academy at West Point and the U.S. Naval Academy at Annapolis. It was a genuine honor, he says. “They were great listeners, and it was one of the happiest days of my career. When I visited both academies, I went to their museums and saw lots of examples of how R&D investments and technology advances changed warfare. We are witness to similar dramatic transformations in agriculture and the processing of agricultural products.”

Author: Tom Bryan Ethanol Producer Magazine 701.746.8385 tbryan@bbiinternational.com

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Andrew Hawkins, director of laboratory services at Phibro Ethanol Performance Group, likens control charts to a two-lane highway. Drivers on a winding country or mountain road, he says, know they’re in their lane because they haven’t passed over the double-yellow center line or the white line marking the side of the road.

“The control chart is almost exactly like that,” Hawkins says. “It’s a statistical derivative or version of that. Where you’ve got the centerline, that’s the double-yellow line, and then you’ve got an upper control limit—which is three sigma—and you’ve got a lower control limit—which is minus three sigma.”

Control charts aren’t new. Hawkins says they were developed in the 1920s but came into wide use after World War II as manufacturing became more complex. They were particularly helpful during the space race, he adds. “NASA had tens of thousands of steps that had to be done, and they had to be done with great accuracy through a process,” he says. “That’s when statistical methods like the control chart where actually more widely adopted. They’re used to kind of visualize your data, which gives you kind of a quick overview of whether something is out of whack, in process or normal.”

While they’re not new, Hawkins says he isn’t sure how widely they’re used within the ethanol industry. But, he adds, there is interest among plant and lab managers about how the tools can help ethanol operations. Following a presentation he gave last fall, Hawkins says many of the questions were about control charts. “People were inquisitive about the tool and how it could help them,” he says.

Hawkins says control charts are useful for processes that are repeated. With 20 results in hand, control charts really become useful, he says. “They’re really a way to visualize process data that you’re doing repeatedly—things that you do every day or every so often,” he says. “It’s a way to visualize the results of a process or a machine and then be able to visually indicate when things are working as they should—or in control—or when you might have an excursion or a process upset, or an instrument upset.”

Knowing those upper and lower limits, and when plant machinery is operating within those limits, allows a plant to fine-tune its operations, Hawkins says. “By leveraging control charts, you can really find when things are in control, or hovering around that centerline where you would expect to be, and whether or not you have really wide limits, or really narrow limits,” he says. The result of that fine-tuning, he explains, is represented by data being closer to the center, or “hugging the centerline” in the road analogy. In Check

Kristi Plack, chief science officer at Bion Analytical, says control charts are “a great way to monitor each instrument over time to see if you’re seeing any trends.” Repeated deviations from an instrument’s true value would require a deeper look to see where the issue lies, she says.

Hawkins agrees. “[Control charts are] a way to generate trends, and statistically, it’s a way to view the trends of your equipment so you know whether or not your pH meter or your HPLC is functioning,” he says.

Control charts are also useful for visualizing natural variability in lab data, Hawkins says. “There could be a hundred different reasons why, when you run a sample on the HPLC today, it reads 1.05, and when you run it again tomorrow it reads 1.01,” he says. “But the question is are those two numbers within the expected natural variability or do they indicate that the machine wasn’t working yesterday or maybe it isn’t working today. And so, it kind of allows you to appreciate that and put those results in context.”

And while control charts are a statistical tool, which may seem daunting to some, Hawkins says they can be used without understanding the math behind the results. He explains that software programs and templates like those made by the American Society for Quality, and others, don’t require users to derive the equations to use the tool. “You don’t need to know the theory behind the power drill, you just need to know how to work the power drill,” Hawkins says, adding that he doesn’t have a background in statistics but makes regular use of control charts.

Keeping the charts easy to use is important, according to Plack. “I would make sure that it’s something that’s not burdensome to someone, because we all know what happens there, right? You end up not using them,” she says.

Hawkins agrees. He says it’s possible to generate control charts by hand, but he doesn’t recommend that method. “You can actually learn how to generate them without deriving the equations,” he says, adding that a program called JMP is one option, as is Excel.

“It’s not hard to do in Excel, which everybody has on their computer,” Plack says. “It’s just making one, and then once you have one made, you can tweak it for the next one.”

Fine-Tuning

As plants make more incremental changes to efficiency and operations, control charts can help guide those changes. “I think more and more people are realizing—especially as margins be-