Optimizing smart manufacturing data in feed and grain facilities [Video]

Interstates' Jeremy Van Den Berg on Industry 4.0 and best practices for collecting and analyzing feed and grain facility data.

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Elise Schafer, editor of Feed & Grain: Hi, everyone, and welcome to Feed & Grain Chat. I'm your host Elise Schafer, editor of Feed & Grain. This edition of Feed & Grain Chat is brought to you by WATT Global Media and Feedandgrain.com. Feedandgrain.com is your source for the latest news, product and equipment information for the grain handling and feed manufacturing industries.

Today I'm joined on Zoom by Jeremy Vandenberg product manager I-Control for Interstates. He's here to talk about smart manufacturing in grain processing settings. Hi, Jeremy, how are you?

Jeremy Van Den Berg, product manager I-Control for Interstates: I'm well, Elise.

Schafer: Well, let's get right into it. Can you describe the concept of smart manufacturing in the context of feed milling and green processing facilities?

Van Den Berg: The concept of smart manufacturing or sometimes referred to as industry 4.0 involves the introduction and integration of advanced technology to enhance efficiency, productivity, and flexibility into manufacturing process in this case, specifically feed and grain The goal of smart manufacturing, in my opinion, is that facilities can gain increased efficiency, waste reduction, better product quality, and increased overall sustainability at their facility. We see in this industry, we see people seeking to do more with data searching for ways to speed things up, find the shrink, find downtime, improve the recall scope, as well as optimize the production process to meet customer specification.

Schafer: Now what kind of equipment and instrumentation should be integrated into a smart manufacturing system to maximize its value for the user?

Van Den Berg: A lot of times the effort centers around adding sensors, devices or equipment to gather the real time data on your process. The environment you're in or product quality. The sensors could vary from NIR devices to utility monitoring, to not even sensors but deeper integration between business and manufacturing software packages or devices. Software aimed up predictive maintenance doesn't mean to add a sensor just for the sake of gobbling up and logging every possible thing. But adding devices and equipment to attack the problem or achieve a specific goal, keeping in mind that the answers you get from some of these devices could only could prevent keeping in mind that the answers you get from these devices may produce new questions. So staying purposeful in that and equipment and the instrumentation that you add is key.

Schafer: Now integrating these processes and instruments produces an incredible amount of data. So how critical is the data analysis component to smart manufacturing and how does this translate to ROI for system users?

Van Den Berg: It absolutely produces a lot of data and knowing what data is important and should be analyzed is key. Asking yourself what is my ideal end result? Or what problem am I trying to solve is usually the best way to start. This will help you kind of sift through what data has been collected and know just what could provide value.

What you want to avoid is aiming to be a plant of the future and add ways to measure everything thinking that it will organically provide insight. More often that leads to adding little value because you become paralyzed by the sheer amount of data. So knowing the answers to the questions I mentioned earlier about ideal result, or the problem you're trying to solve is how I see an effort in this space and in Smart Manufacturing translating to an ROI.

A simple example would be if you wanted to reduce energy consumption because you were getting hit with peak charges from your utility. Knowing what times you tend to draw high amounts of power, what equipment was running, or even what product you're trying to produce at the time when that utility has increased rates that could potentially help find ways to reduce your energy consumption during those times and translate to that ROI you're looking for drawing those correlations between your problem and what is measurable or could be captured. That's the critical part of the data analysis.

Schafer: Well, Jeremy, thank you so much for your insights today on Smart Manufacturing.

Van Den Berg: You're welcome. Thanks for having me on.

Schafer: Absolutely. That’s all for today's Feed & Grain Chat. If you'd like to see more videos like this, subscribe to our YouTube channel. Sign up for the Industry Watch daily eNewsletter or go to feedandgrain.com and search for videos. Thank you again for watching and we hope to see you next time!