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Eggheads is the go-to podcast for egg industry professionals who are interested in leadership and innovation in the egg world. Host Greg Schonefeld explores the evolving world of modern egg farming, from the latest in cage-free innovations and organic certifications to navigating the economics of large-scale production. Whether you're an egg producer, supplier, or involved in poultry genetics, this show provides the insights and expert discussions you need to thrive in the industry. Crack open the science, strategies, and stories behind the egg industry’s biggest challenges and opportunities.
Bill Bretschneider:
There used to be a person on the end of every packing lane. As these machines have gotten faster and faster, you get into 20 and 30 packing lanes, you'd have 20 to 30 people back there. Nowadays, you have one robot covering two lanes, so really one person can take care of two to three robots at once. So now you got one person covering six lanes.
Greg Schonefeld:
I'm Greg Schonefeld and this is Eggheads. Artificial intelligence has become a huge buzzword in pretty much every industry, and the egg business is no exception. But while many companies talk in general terms about how AI is going to do things like streamline operations and supercharge productivity, today we're looking at a company who's implementing the technology in ways that are much more tangible.
Bill Bretschneider:
My name is Bill Bretschneider. I'm with Moba. I'm a product manager. Been in the egg industry for 42 years now.
Greg Schonefeld:
Moba, a company based in Barneveld in the Netherlands, is one of the world's biggest suppliers of egg grading, braking, and sorting equipment. And Bill, with his decades of experience, essentially acts as their eyes and ears in the US market, a market that's become a bigger and bigger part of Moba's business, especially since they acquired a company called Diamond Automation in 2009.
Bill Bretschneider:
In the US, I would say Diamond was the biggest player at the time. Moba was very big in Europe and they looked at the acquisition of Diamond as a good way to get into the US market. We merged the two companies together and now we became one of the biggest producers in the US of this sort of equipment.
Greg Schonefeld:
Moba makes equipment for every stage of egg processing, from the time they arrive at the facility to the point where they're ready to be trucked to the grocery store. When Bill joined the industry in 1984, all of these jobs were done by people. But over the past 40 plus years, he's watched the technology evolve to the point where most of these tasks are handled by machines. Today, he walks us through the history of that automation and what needs to happen for a truly light off egg processing facility to become a reality.
I'm guessing every step of that way that's automated, there's a story behind it.
Bill Bretschneider:
Oh, absolutely.
Greg Schonefeld:
Like this didn't all happen overnight.
Bill Bretschneider:
No, it's correct. I mean, when I started in the egg business back in '84, there were people doing all of these jobs. So you can imagine initially there were humans that candled eggs. So a human actually had what we called a wand, and they would look through a candling light. They would go over these lights and they would tap on the egg and push one button if it was a dirty, they'd push a different button if it was a crack. You have two people in the booth and humans generally tend to talk. So they would start looking up and talking to each other and eggs are going by and they're kind of missing them. With the modern systems, they don't have to take a break for lunch or anything like that. They just keep inspecting. They don't sneeze. They don't have to go to the bathroom. So really it's kind of helping the producer make a better product, but it's also making their dependence on labor easier.
Greg Schonefeld:
Yeah. You take away a labor need, but then at the same time, you're getting more accurate and faster.
Bill Bretschneider:
For sure. And then you look at something like the case packer. I mean, you would have a human in the old days that all these packs would be coming up the line. All day they're bending over and picking up packs and putting them into a box. Humans make mistakes. They can accidentally drop one. They could pack them a little rough where the robots always pack them at the right speed. They set them in nice and soft. They don't make mistakes that humans can make.
Greg Schonefeld:
So when you're deciding what problem to solve next, is it just a general pain point? Is it a major cost thing? Or like a, "Man, I just can't find people for this anymore" type of thing?
Bill Bretschneider:
It can be a combination of any of those, to be honest. I mean, at Moba, we try to listen to our customers all the time. That's part of my job is to just, what's the next hurdle that you guys are struggling with? Depending on where you're located, it could be people. Food safety is always a big concern. We're just keeping our eye on the market and trying to keep in touch with our customers and see what they need next to try and stay on top of it.
Greg Schonefeld:
Yeah. Well, I think that's one interesting story, is the salmonella outbreak that happened a few years ago and how that led to innovation. Can you walk us through that?
Bill Bretschneider:
So when the whole salmonella outbreak happened, all the systems that were doing crack detection and weighing actually touched the eggs. The salmonella outbreak got traced to a particular plant. And what happened is the USDA looked at the rules for cleaning machines. They made it more stringent. And so the old areas that a lot of the suppliers thought were really good areas were very delicate and very difficult to clean. So you kind of needed a specialist to get in there and clean them than a regular cleaning crew that generally comes in at night. So that became a big problem for our customers. And that's what really led us to step back and go, okay, how can we weigh eggs more efficiently, cleaner, a way that's easier to take care of, both weighing and correct detection?
Greg Schonefeld:
Oh, that's really interesting. So the USDA actually had a specification at that time of what needed to be cleaned and it changed after the salmonella outbreak.
Bill Bretschneider:
That's correct. So there were a couple of different types of systems out in the field at the time. There was what Moba had, which was a system that had plungers from above and actually tapped the eggs. It was a steel ball that was in a little plunger. So this plunger would come down and just tap the egg and the little metal ball floated on a magnet. So it just would tap the egg and there's a microphone. It would listen to the sound that the egg made when it was tapped, and then it would determine if that spot was cracked or not.
Greg Schonefeld:
Interesting. But then every one of those little pieces could need to be cleaned then.
Bill Bretschneider:
Well, so you think about it. I don't remember the exact number, but each row had, I would say, 16 to 18 tappers. So multiply that by 18 rows wide. So each one of these was mechanically actuated to fire and touch the egg. And then if you didn't keep those clean, they could stop tapping correctly. So it was just a lot more maintenance. You'd have to actually pull the plungers out, get in there with a little vacuum and clean them out. Nowadays, it's just a sealed camera system. The cameras are in an enclosure and they're looking down on the eggs. So when you go to clean the rollers and parts around the machine, there's two doors that shut. Basically keep everything protected inside the camera box. So it went from all of those parts to very simple.
Greg Schonefeld:
Touching's been taken out of the process. Cleaning is dramatically reduced and simplified. Has any accuracy been sacrificed in that process?
Bill Bretschneider:
No, actually the systems have become a lot more accurate. If you think about it, if there was a little speck of something on the egg, maybe where you were tapping the egg, could give a false number. Now the eggs are back lit. The cameras are looking at the eggs and you can see everything about the egg. So it really doesn't miss.
Greg Schonefeld:
And so this is vision powered by AI making that possible?
Bill Bretschneider:
That's correct.
Greg Schonefeld:
Okay. Is that one of the first major problems that AI solved?
Bill Bretschneider:
For Moba, it was. It's interesting because we use AI on our vision crack detection. We use AI on our vision weighing, and we also use AI on our dirt detection. We call it our egg inspector. And actually, if a customer has a slightly different shell defect that they want to sort out, they can come to us with samples of that and we can teach the system to find these particular types of defects. So it can determine the difference between regular brown dirt, white dirt, egg yolk, holes in the eggs, like wrinkly type shells, calcium spots on the shells. And those can all be said differently. So the old systems, you would see something. You would see a spot on the egg and you could decide how big or little of a spot you wanted to pull out. Now you can look by each defect and set the settings differently. So it's really come a long way.
Greg Schonefeld:
Wow. If people think ag doesn't adopt technology fast, it seems like, man, ag was right on the AI wave here.
Bill Bretschneider:
Oh, for sure. I mean, we're looking at other things now as well with AI. So we're looking at more proactive troubleshooting, having the machine kind of monitor its own systems. And if it starts to see something happening, it can predict what's going to be happening based on inputs that it's getting from the basic devices on the machine.
Greg Schonefeld:
So what kind of things would it predict?
Bill Bretschneider:
Just as an example, if the motor was always pulling a certain current and all of a sudden the current started going up that something's happening, that it's making it pull harder, something's going on there. So you could have a team looking at that and, okay, what could be happening here? And you can flash a message up to say, it's time to take a look at this or maybe you need lubrication. Maybe it's a part that's going to be failing. And this is something that we're starting to look at, but it's early in the process.
Greg Schonefeld:
Yeah, that's really interesting. In the competitive landscape, is everyone kind of looking to solve the same problem at the same time and you're racing to get there? Or is everyone just kind of working a little bit more in isolation?
Bill Bretschneider:
Well, I think Moba's been a leader in this. I mean, we were the first to come out with the vision crack detection and the vision weighing. So competition gets wind of that and they want to start working on them as well because everybody's asking about it. It's the new hot thing and it makes cleaning so much easier and there's less parts to use for repairs and on and on. So it becomes very attractive. And once they see the advantages of it, everybody kind of wants it.
Greg Schonefeld:
The advantages of this new tech seem pretty obvious to me. It's both faster and more accurate. It's easier to clean and it gets rid of the need to source labor for all these jobs. So I wanted to know, does that mean adoption is pretty much automatic once the tech is improved?
Bill Bretschneider:
There's still a lot of old machines out in the field. I mean, there's machines that. Back in '84, I used to hand build a lot of the electronics in the old Diamond 8200s. And I see them all the time out in the field. So they're still out there. They're still running.
Greg Schonefeld:
I guess some of that old machinery must be functional and economical enough that it's not worth it to the farm to replace it.
Bill Bretschneider:
I think in some cases, customers do have the funds to be able to replace them, but they're comfortable. They know how to take care of them. They know how to clean them. They know the advantages of the new stuff, but they're very comfortable in what they're doing in their current process. So changing to the AI is scary for some customers.
I'll say this. I mean, back when I started in the industry, I would say the standard guy that was hired at an eggplant to be the repair manager on the machine was generally an auto mechanic. And so the machines were more mechanical back then, less electronic and less things like vision systems that are AI stuff. So those type of guys are really comfortable with these older machines. You need more an electromechanical person that's on top of the newer technology to be able to service these new machines. And with Moba, we have a technical training center right in our facility in Michigan. So for customers that do change over, they can come in and get classes on various parts of the machine and get them up to speed pretty quickly.
Greg Schonefeld:
Interesting. So I guess I'm thinking of some people are just car guys and they like their '95 Ford or whatever because they know how to fix it where the new ones have computer chips that they don't want to touch.
Bill Bretschneider:
I mean, if you've been working on the same machine for 20, 30 years, you know pretty much this happens, it must be this that's going on. So change is a little scary to people like that.
Greg Schonefeld:
Do you think that's a missed opportunity in some cases that there are some cases where a producer might be better off upgrading to the new technology but don't?
Bill Bretschneider:
I do. I just think that the way that the systems work these days and how accurate they are and the crack detection, you set it up and you just run it. There's really no calibration to it. Same with the weighing. When you get into the mechanical systems, there's all this cleaning, there's calibration, there are parts that go bad. All these sorts of things that can affect you during the regular shift.
Greg Schonefeld:
One concept that we've talked about on the show before is this idea of a lights out plant where the owner just has to flip a switch and robots can handle everything completely autonomously with little or no human intervention. And with the innovations Bill has described to this point, it doesn't sound like that's too far away from becoming a reality.
Bill Bretschneider:
So I think what you're seeing these days is you're seeing the need for less and less people. So the automation, like the robotics on the back end, there used to be a person on the end of every packing lane. As these machines have gotten faster and faster, you get into 20 and 30 packing lanes, you'd have 20 to 30 people back there. Nowadays you have one robot covering two lanes. So really one person can take care of two to three robots at once. So now you got one person covering six lanes. We talked about the people that used to be in the candling booth, now with that modern technology, they're gone.
So what I kind of see is, I don't know how quickly it'll happen, but you're getting less and less people needed in the plant. I envision that before the lights out, it'll get to where there's maybe two to three people that are around the plant and they're basically in a keep an eye on the machine type mode, bringing in materials and things like that, just kind of monitoring what's going on. But the reality is with the systems that we have, I mean, we have a platform called iMoba where you can be in an office on the other side of town watching what's going on with your machine. So I mean, we're getting there slowly, but how quickly it'll happen is difficult to say.
Greg Schonefeld:
What are the major things that haven't been automated?
Bill Bretschneider:
So like right now, what really isn't happening in the US is like filling the denesters with cartons and trays and things of that nature. There's humans doing that.
Greg Schonefeld:
What's a denester?
Bill Bretschneider:
That's where you load your cartons or trays that the eggs get packed into and they get stacked in there pretty high. So they nest down one at a time. They go down a little conveyor and then the eggs are placed into the package. So the denester is what holds a bunch of those before they're fed one at a time.
Greg Schonefeld:
Okay. So that's loaded manually.
Bill Bretschneider:
Yep.
Greg Schonefeld:
Okay.
Bill Bretschneider:
But there are customers outside of the US that are starting to get into automatic denester loaders as well. So there's stuff out there for sure.
Greg Schonefeld:
Interesting.
Bill Bretschneider:
What you're starting to see too though a little bit is, so right now most places have fork truck drivers, but now you see these little automatic fork trucks that you can set up a path in the plant. They'll actually come and pick up pallets of eggs out of the palletizer and take them and put them in the proper place. That's something that's starting to roll out in the industry.
Greg Schonefeld:
On top of those little tasks that haven't yet been automated or haven't been automated everywhere at least, Bill says an important role that human beings continue to play in these plants is monitoring.
Bill Bretschneider:
Well, like I said, it could be not just a machine issue. It could be a material issue. So if you get a big bundle of material that's automatically loaded onto the machine and somehow in delivery, something happened to part of it. The machine's just going to put it on. And if it's not correct and say a carton's torn, it gets caught somewhere, it's going to stop the line until somebody does something about it. So there's just things like that that aren't necessarily in people's control and they're keeping an eye out on all that stuff.
You think about pulp material that's used on the machines. It can swell up when it gets humid. It can shrink down a little bit. So that causes different things to happen, makes them harder to nest sometimes. So there's just little day-to-day things that can go on like that, that people watch for.
Greg Schonefeld:
Okay. So yeah, when there's high variability like that or just things that are hard to predict, that's where you need the people.
Bill Bretschneider:
Yeah, I'd say so. I mean, there's so much going on in a plant and there's just a lot to keep an eye on for sure.
Greg Schonefeld:
One other thing you mentioned there that's interesting tech, I think you called it iMoba, but that's where you can actually see what's going on in your plant offline or from anywhere in the world basically.
Bill Bretschneider:
Yeah, it's kind of neat. So there's different apps as part of iMoba. One is like a widget tool. You can just monitor your top three or four or five things. What's the speed? Is it running? Yes or no? Where's my production at for the day so far? Things like that. Then there's other things that are more performance related. We have a benchmarking tool that if you're signed up for iMoba, you can compare your performance with random other machines that are like yours. It won't say who they are. But for example, if you have a Omnia PX 530, you can kind of select, okay, I want to inline 530 and select this criteria. And it'll say the number of cracks that you're getting through your machine is somewhere in the middle or you're really high compared to a lot of customers. So that can make them look back at the eggs that are coming up onto the machine to see if they have areas where the eggs are getting cracked. But just for a customer that's got one machine, it's really a nice tool to be able to see, how am I doing?
Greg Schonefeld:
And another exciting new product that Moba's rolling out aims to deal with an issue that a lot of producers face as their operations become increasingly high tech. And that's the fact that they have all these different systems running at the same time that aren't always compatible with one another.
Bill Bretschneider:
Nowadays, a lot of the machines that we supply, like the robotics and so on, don't necessarily talk to each other right now. So with the new platform that we're coming out with called Magna, it's actually out already, but the idea is to get all that control in to the user interface on the machine so you can see what's going on on each piece of equipment.
Greg Schonefeld:
What different pieces of the equation might be coming from different places and not be naturally interconnected without Magna?
Bill Bretschneider:
So if you think about it, like an offline facility, generally the depalletizer and the loader is in another room. Customers will generally have what we call like a wet room and a clean room. And so where the washers are and the accumulator and the loader and everything and the initial part of the machine is kind of more a wet area. It's a loud area. They'll put a wall in between there. So you're not necessarily always on top of what's going on in that other room. So just the Omnia, which is the platform that Magna's going to be replacing, has been around for a long time and it just didn't have the technology available to tie all this stuff together. So that's something when we came out with Magna that we wanted to incorporate into the new machine.
Greg Schonefeld:
And you can do that today, whether it's your machines or not?
Bill Bretschneider:
We are looking to link other machines as well. And again, we're early in on this process, so it's definitely something we're looking to do.
Greg Schonefeld:
I guess I'm getting this picture that the technology is just moving faster and faster. I mean, I guess, is there one thing in particular that just has you really excited for maybe the next three to five years in your world?
Bill Bretschneider:
I'm really excited about the predictability that we're looking to incorporate into the machines so it can kind of see what's going to be happening down the road. Take different inputs and figure out that this means that and that maybe you need a better job of lubricating this area or a part that's going to be failing, things along those lines. So instead of becoming reactive from a service standpoint, you're becoming more proactive. So when you're done with the shift for the day, you can go in, let's figure out what's going on with this and see if we see something happening. Where in the old days when you didn't have that, it just stopped and something broke or something along those lines. So again, being more proactive than reactive, I think is a good way to say it.
Greg Schonefeld:
What stood out to me talking with Bill is how automation takes shape in agriculture. I think ag has a really unique challenge in needing to combine the unpredictable nature of biology with automation. It's enlightening to hear how tech has evolved over the years in this egg processing space, solving one problem at a time, which has led to one of the challenges of today, making sure all those solutions communicate with one another and work in tandem. And another thing I find exciting is the emergence of AI. It was great to hear what it's already done to help the cleaning problem associated with the salmonella outbreak, and I'll be interested to see what problems it can solve in the future. And now having covered everything from crack detection to depalletizing, just one question remains.
Bill, I have one last question for you. How do you prefer your eggs?
Bill Bretschneider:
I love omelets. I got to say, I have an omelet every day.
Greg Schonefeld:
I could see the real passion on your face.
Bill Bretschneider:
Oh yeah. It's the best. Little stir fry with veggies and then ... Oh yeah, love it.
Greg Schonefeld:
If you enjoyed this episode, please share it with a colleague or friend. Word of mouth really helps us to grow the show. And to make sure you don't miss an episode, follow us on Spotify or Apple Podcasts. Until next time, I'm Greg Schonefeld and we'll talk to you soon.