Industrial Automation – It Doesn’t Have To…
Join us as we explore all things Industrial Automation. Brandon Ellis, owner & president of elliTek, has seen the good, the bad, and the great when it comes to automation. We'll delve into the challenges that manufacturers face, find out what it doesn't have to..., and have some fun!
Industrial Automation – It Doesn’t Have To…
Industrial Automation - It Doesn't Have To... Be Hopeless
This episode is about thankfulness and gratitude. Industrial Automation can be hopeful and positive.
elliTek is thankful for each of our customers, our colleagues, and our families.
During this episode, we review some projects that our customer's have told us that they are thankful for and that they have benefited from.
Hopefully, you will come away with a fresh idea or perspective that can make you hopeful.
The types of projects discussed are as follows:
- IoT Based Projects
- Smart Assembly Pack Out Systems
- Material Handling & Management
- Automated Robotic Handling
Stick around to hear the four reasons to automate according to Brandon's Brandology.
Brandon Ellis 0:24
Good morning, afternoon or evening according to when you're listening to this podcast. This is Brandon Ellis, with elliTek and Beth Elliott.
Beth Elliott 0:32
Hi guys! How are you today, Brandon?
Brandon Ellis 0:34
Doing good, Beth. So today is season one, Episode Six,
Beth Elliott 0:39
Six already.
Brandon Ellis 0:40
Yeah, the sixth podcast of Industrial Automation - It Doesn't Have To. And so I want to thank everybody, we've been having a really good amount of downloads and, and interaction with you guys. And so we're having a lot of fun. And I appreciate you all, taking time to be a part of this thing and have fun with us. Hopefully you're learning some stuff with us. And then also sharing with with people that you know, spread the word.
Beth Elliott 1:03
That's right. So what are we going to talk today about, Brandon? I think it's the Thanksgiving season. So this episode, we're gonna name it Industrial Automation - It Doesn't Have To... Be Hopeless.
Brandon Ellis 1:19
Hopeless. Yeah, that doesn't sound like a very good Thanksgiving theme. But it doesn't have to be hopeless, which means it can be hopeful. So yeah, we're coming into Thanksgiving, actually, when this hits, it will be Thanksgiving week. So hopefully everyone that's listening to this has, is preparing for a wonderful, wonderful Thanksgiving time with family. I know there's a lot of question marks this Thanksgiving because of this Corona pandemic that we're all dealing with. But hopefully, when this episode finds you that everything is good with you, and good with your family, and everyone's healthy. So far, our family's healthy and our our employees are healthy. And I think for the most part, our customers are healthy. And so for that we're really thankful.
Beth Elliott 2:04
Yes, yes. And so I think we want to focus on the positivity. What's going you know, you got to find something positive.
Brandon Ellis 2:12
You know, the last few podcasts that we've done, I think we've mentioned trying to be positive. Because this has been a crazy, crazy year, Who would have ever known that 2020, you know, the year to see clearly. Boy, I don't I didn't want to see this clearly. Did you? This is that I was happy being less clear. So we're, in fact, I was having a conversation with one of the ladies at our church about the upcoming planning for Christmas, the Christmas programs for the kids and things of that nature. And I'm one of the musicians and so
Beth Elliott 2:49
What do you- what do you play?
Brandon Ellis 2:50
I play a plethora.
Beth Elliott 2:52
Okay, very nice.
Brandon Ellis 2:54
You like that word?
Beth Elliott 2:54
Yeah, I do.
Brandon Ellis 2:53
I've actually learned that from the movie Three Amigos with Chevy Chase, Martin Short. Steve Martin, I think, anyway, yeah, I play guitar. I play drums. I play bass. I'm probably other three of those. I struggle most on the bass. But the guitar is my certainly my first instrument. But anyway, she was asking me, have you heard anything about the upcoming and I said, Of course in jest, I think we're gonna skip Christmas this year, and just focus on New Year's Eve. Because we're ready for 2021 say, you know, let's, let's put that in the rearview mirror and move on. So we want to make sure though, that we are thankful. And we are very thankful. We're thankful to our customers, I'm very thankful to our employees and their hard work this year, as we've dealt with a lot of a lot of things.
Beth Elliott 3:02
A lot of uncertainty.
Brandon Ellis 3:41
Uncertainty, working remotely, trying to keep up with all the rules and stay healthy and clean and figure out new ways to to be respectful of other people's spaces and things of that nature. And so it's been a challenging year for a lot of folks. But, but let's go ahead, let's go ahead and go through this. So, so it doesn't have to be hopeless, which means the theme that I was kind of asking you for, was to basically review some things that we've gone through with customers, that I feel like that our customers who have commented in the recent past about how I'm thankful that we had this capability, or we were able to do this project or, or see this success and kind of talk about what those are. Because those a lot of those projects. You know, it's interesting, when someone asked me Tell me about a project you did that was really this or that or the other, you know, really helpful or something or really a great IoT project or robotic project. Tell me about that. And then I'm just a blank I draw a complete blank. But if you're just having conversation with me, as you know, if someone says you know that they were wanting to do something like this, I can recount recount three or four. Well, that's just like what we did for this person or that person or these different things. And so it's interesting, the way my mind works, is least is my memory works. So we've kind of gone And trying to put together a few categorical things and kind of talk about projects within those. So hopefully this will be of interest.
Beth Elliott 5:07
I think so. I think the first ones we're going to go over are the IoT based projects. So do you want to discuss one of those projects?
Brandon Ellis 5:18
Sure. Sure. Sure. Are we? Well, IoT, so IoT, we was at our last podcast? No, it was a couple podcasts ago.
Beth Elliott 5:25
I can't remember.
Brandon Ellis 5:27
The last one had to do with TEEP and OEE, and that kind of stuff. Yeah, that's right. I think it was the one before that we were talking about IoT. We've talked about it in terms of, and well, even the last podcast, we were talking about OEE and OA, and all those kind of things. And I'm using the acronyms on purpose, because you can go check that out in our podcast. But a lot of those things can be derived in manual ways. But they can also be derived, derived as part of an IoT system, Internet of Things is IoT. And so industrial Internet of Things is what I'm referring to. And so in doing that, an IoT based project as an example, that comes to mind as a final final assembly type traceability project,
Beth Elliott 6:04
Okay, Do you want to go over traceability? What that is?
Brandon Ellis 6:07
Sure, sure, sure. So the the traceability portion, You know, as I've talked to folks, customers, various customers that are in - they're endeavoring to have an IoT based system, and they ask me, What are some of the IoT stuff that you've done? And I've told them about traceability. Inevitably, a lot of them will say, we're not even to that level. We hope for that. We're just trying to get connectivity to our machines. I guess the IIoTA, our IIoTA product is just so stinking easy that I don't really consider this a second level of integration.
Beth Elliott 6:41
Okay.
Brandon Ellis 6:42
I consider it kind of a pretty easy thing to do, because it's point click, but if you're using another means of that, or you're trying to do it manually, it's nearly impossible.
Beth Elliott 6:51
That's labor intensive.
Brandon Ellis 6:52
Well, it's also programming intensive, because the way we used to do this is it again, so so let me lay out the concept. So in this case, traceability normally for me, in final assembly situation - final assembly, meaning we are going through the final steps of finishing the good, the part that we're going to sell. And so the final steps is usually in an assembly line operation more than one step more than one person more than one process. Remember, processes are machines now in the last podcast, and it bothered me so much, but I just that day had in my mind, the word defect stuck in my mind. And I was talking about machine faults, and I kept saying defect, and I corrected myself a couple of times. But as I re-listened to the podcast, I said it again and again, and again. I just had defect in my mind. Defect is a product problem, not a process problem. Process problems are faults usually, is how we talk to them
Beth Elliott 7:48
With the machines?
Brandon Ellis 7:49
With the machine. So a process is the machine usually, or a human thing. But it's an action actionable thing that's going on, it's not it's an activity that's being enacted upon the product.
Beth Elliott 8:01
Okay,
Brandon Ellis 8:02
So the product is the car, I'll use car again, the product is the car, the process is putting the tire on securing the lug nuts of the tire. So if you if you do that wrong, this fastening process, you have a fault in your process, if it damages the lug nut or the stud or whatever, the tire, then you've created a defect of the product. Okay? And so defect is product - fault is the process. And the that's important. So forgive me for if you listened to that, if you haven't listened to it, I don't know, every time I say defect, take a drink. Give somebody a hug. I
Beth Elliott 8:42
No! Oh, that was too loud.
Brandon Ellis 8:45
Don't do that. It's a new normal, don't hug, no hugging, give them a fist bump or an elbow bump or something anyway, so so that said final assembly product traceability. So in this scenario, we had a final assembly situation, where we had multiple, we have multiple stations or processes, some are completely, completely automatic, except the person is putting the party and hitting go and walking, you know, moving we talked about walk time and that, or it's totally manual, they have a fixture, they're doing some assembly and that kind of stuff. And when they get done, there may be sensors on the machine to sense things are being put in the right place, that kind of stuff. But then when they're done, they hand it down. And there's traceability. So we're scanning a QR, you got to have a means of identification, unique identification for the product. And that's why I think sometimes people think this is second level integration, because you have to prep you have to prep a little bit. So your product does have to have a means of tracing it to know to differentiate between this product or that product. So a serialized barcode or QR code or something is a way to do that. So the concept is and traceability is you want to make sure that it follows a predefined process flow - process work order, it goes to process A and then B and then C and then D before it goes to E. If you're at A and B, but you skip C and try to go to D, you want to communicate with the machine at that point or the process, the operator even has like a buzzer some kind of notification to say, No, you you skipped, we call that skip process.
Beth Elliott 10:15
Okay.
Brandon Ellis 10:16
So in our in our traceability, we refer to this as skip check, which we're checking to make sure you didn't skip a previous process. So skipping a process is one thing, but also what if you fail the quality checks of a previous process. And so process A, process B, process C, you go through C, but you fail it. So the machine or the process is able to check, and it says this is not pass quality. There's a problem. Maybe it was a robot that was doing a solder inspection and inspected the solder wrong. Maybe it was a weigh scale system that's looking at something that says I expected to see this much material and it's not there, though, whatever, something wasn't right. And so the machine said, you know, red light came on and said we've got a problem reject that part. Inevitably, it made it down to the next station. That's the scenario. And so now it went. So that was processed C. So now it's at process D and the operator introduces it at D and traceability says when they scan it, it checks back and says, Did you go through C? And did you pass successfully the quality checks? And if the answer is no on either of those, then it will not let it continue on. So we talked about defect flow out prevention. So that would be a preventer at that. Because we're midstream. We're mid assembly, and we're stopping it from continuing to be built. Because at that moment in time, we know that we're going to make a perfectly bad part. And we're going to burn up perfectly good labor and perfectly good materials on downstream perfectly good resources to make a perfectly bad part. So it's not a question of it's it is, but it's not solely a question of will a bad part go out the door. It's a question of how much did this making of a bad part cost us versus what we could have made in good parts? Remember TEEP?
Beth Elliott 11:59
Yes.
Brandon Ellis 12:00
Alright, so that's traceability. And and it's in, because we're checking back, it's built into the edge based system of our IIoTA. IIoTA stands for industrial Internet of Things Appliance. It's our product - it's a fantastically simple product, one we would love to work with you on, but it has this built in. What we used to do, and I started down this path earlier, what we used to have to do is we'd have to get all the PLCs, if they're PLC based on those machines, all those processes to check back with the previous one.
Beth Elliott 12:27
That seems like it would take a while.
Brandon Ellis 12:29
it's not horribly bad. If you have one PLC, what we call a central centralized PLC processor, who's controlling all the processes, but that's not really feasible. Because a lot of times different lines have different processes. And sometimes this process was one that we've been doing for the last 10 years. And this is a process we just started. This one's 10 years old, it has an old PLC that we don't standardize on anymore, or we haven't used that in forever, or it got built in another plant or, you know, usually the realism is, if every manufacturer every time there was a line got to create all new product, no, or order all new equipment, that would be great. Not feasible. Most manufacturers are savvy.
Beth Elliott 13:12
They gotta be.
Brandon Ellis 13:13
They gotta be. And so they, they, they if they've got equipment that this, we use this on line six, and we took line six out last week, because you know, last year, whatever, because it's not products not being made anymore, whatever. But we could still use that one process that one machine for on this new line. So let's integrate that in and not have to pay again, or get a new machine built, if that machines still usable, can be retooled or things of that nature. So that makes that difficult because you have potentially incompatible PLCs. Maybe they're legacy maybe they're just different. Maybe they just don't talk don't support the same kind of things. And so it was always a challenge. And that challenge has gone back two decades for me. The fact that IIoTA can talk to multiples and legacy devices, makes that easier. Now, this isn't supposed to be a sales pitch for IIoTA. But that's the reason why I want to want to give reason as to why I don't feel like this is a second level integration. Because if you're an Allen Bradley person, and you know what PLC fives are we support that.
Beth Elliott 13:15
it's an old one?
Brandon Ellis 14:09
Oh, yeah.
Beth Elliott 14:09
Okay.
Brandon Ellis 14:11
If you're a Siemens person, and you know what S5 is, we support that - we will connect to those things. But at the same time, if you're Allen Bradley and you're talking about ControlLogix, CompactLogix, GuardLogix, all that kind of stuff, that's the new stuff - we support that. If you're talking to Siemens that S7, we got that. If you're talking Omron NJ, NX, we support that. Or we go all the way back to the CS, which is an older platform obsolete platform from Omron. And that's true across the other the other brands as well. That's important stuff because that can save a company a lot of money. So in doing the traceability it's second level, but it helps in a lot of ways from an IoT standpoint. The other thing though, that I've been told is I'm so thankful that I didn't have to upgrade all of my equipment and all my PLCs because your IIoTA product supported these older, these older PLCs.
Beth Elliott 15:01
Wow, that saved a lot of money, huh?
Brandon Ellis 15:02
Oh, a huge amount of money. And the way I see that is, you can see, a lot of times I think people, especially if they're not directly involved with manufacturing, they see savings like that and hear stories of it, of Oh, the manufacturer got to put all that money in their pocket. The way I look at it is that's money that they can reinvest or invest in people - in their people to continue to grow and reinvest in their company.
Beth Elliott 15:25
And, remain competitive.
Brandon Ellis 15:26
Keep competitive, add more jobs, all the things that we're supposed to be about in this great United States and the American dream and all that. That's one of the things was traceability. And then the other half of that is the integration to the upstairs system.
Beth Elliott 15:39
What's that?
Brandon Ellis 15:40
ERP integration.
Beth Elliott 15:41
ERP integration - tell the listeners what ERP is?
Brandon Ellis 15:44
Well, we talked about ERP, in our original IoT podcast, it stands for Enterprise Resource Planning.
Beth Elliott 15:51
Okay.
Brandon Ellis 15:52
It's a software system. So just like we have systems that we're talking about here with traceability, where we're looking at process to process to process to process. In this case, the IIoTA is managing that, to say you went through process A, B, C, and D. And before you went to E, and those kind of things and pass them on those. So the software that talks to all the different systems down there.
Beth Elliott 16:12
And to integrate it?
Brandon Ellis 16:13
What do you mean?
Beth Elliott 16:14
You're talking about integrating the ERP system?
Brandon Ellis 16:17
Well, the ERP system on its own is what I'm getting to as far as its definition. It's a software that controls all the different departments and ties them all together. So when we say Enterprise Resource Planning, or ERP, we're talking about usually an upper level software platform. So let me throw out some names that people would recognize. So SAP, IFS, AS400, those those types of systems that are business - manufacturing specifically, control based software packages, and so they tie accounting to shipping and receiving, logistics departments to purchasing, inventory management, all these different departments that make a company work making manufacturing and manufacturing is one of those. And that's where it's always been interesting is because that's why the IIoTA came to be is because manufacturing with these PLCs, we just talked about Siemens, Allen, Bradley, Omron, all these different ones, they're on the floor, and then the robots and the CNCS. That's a whole whole nother day. They're all on the floor doing the work along with the associates on the floor, to make the finished goods. But they are they're they're disparate systems compared to the ERP base, which is a PC based system and putting PCs on the plant floor - that we got into that and our cybersecurity and so all the stuff that's going on there. So a PC has not traditionally been a hardened enough platform compared to a PLC. PLCs - there are companies out there, there, you're listening to this right now. And you're saying that's right, we still have people that say we still have PLC 5s - Allen Bradley PLC 5s running, Siemens S7s, old, old, old, 12 inch 10-12, whatever size, they were eight to 10, eight to 12 inch, Mitsubishi A series PLCs, those things are still running out there running machines and have been going since the 80s, 90s.
Beth Elliott 16:18
Some horses there.
Brandon Ellis 18:11
Yeah. And, and you can't do that with a PC. This is not built for that. And, and so PLCs are built, they're just different.
Beth Elliott 18:19
They're rugged.
Brandon Ellis 18:20
They're rugged, they really are and, and they're repeatable, and for the most part secure. Anyway, so so the E RP system is usually a PC or software based, server based system, and you need to tie that together, so manufacturing, bringing that system in there. And so the best example of ERP integration then is where we're doing final assembly in this example. And when we finally get through all the processes A through D, or E or wherever I said it stopped. The last process is maybe the operator takes a look at it, maybe they do a visual inspection or something like that, but then boom, they scan it and stick it in the final goods assembly box. And the next stop for that product is out the door on the truck and to whoever the end user is. And so, as soon as at that moment in time, you now have a completed finish good to let the - be able to let the ERP system know that. For manufacturing, we just manufactured one. The ERP system can then kick off with it does and it can it can increase finished goods inventory. It can decrease all the raw materials inventory. It can let purchasing know raw materials is now down below because we just made this this product just put us down below minimum so tell purchasing to start ordering, you know, tell shipping, we've got one ready, all these things that it can do to run the business. And the key is when is the part ready? It all it all leverages on basically that finish good. And so that's what I mean when I say ERP integration. We've had customers that have have thanked us for making it possible for them to integrate with that ERP based system. And a lot of times it was the folks in inventory management and ERP management or even in the IT group that are getting beaten up by the inventory department, or the shipping logistics people or, you know, the department saying we need this information, why can't you get it from us? And And again, it's a it's a bit of a divide to get it from the manufacturing floor. Took longer for me to tell you about that, though I thought it would. But that's an IoT based project. So let's move on to the next category.
Beth Elliott 20:17
Did you want to do another IoT based or just go to the smart packout?
Brandon Ellis 20:21
Let's talk about smart.
Beth Elliott 20:22
Smart, smart assembly packout system. So you kind of alluded to the final product. So what's the smart assembly packout?
Brandon Ellis 20:30
So on the ERP based system, the reason I wanted to break this out, because smart assembly packout systems or smart packouts, they can bring about a lot of a lot of cool things. But they don't necessarily have to be tied in with the IoT system. A lot of the systems, in fact that we've done aren't usually on these systems, it's still you're still doing a final assembly. And I don't know why I honed in on that. But that's just what happened. But when you're doing a packout, or you're doing a final assembly, it ends in packout. Because it's final - assembly. But when I think of these smart packout, smart assembly packout systems that we've done, it's usually for small to medium enterprise manufacturer, the SME manufacturer. And I think so and then maybe they're not small, but what they have is they don't really want to get into they don't have, they don't have so many processes leading up to final as part of the final assembly, they have one and that one may be - okay, I'm going to take a piece out of this bin and a piece out of this bin and a piece out of here, and I'm just going to put them in a fixture and put them all together. I alluded to this earlier, maybe there's sensors and things to say you've got all the pieces in place. So from a quality check, everything's there. They may even maybe even semi automatic, if it's a little bit higher level, where they actually have, maybe they hit a switch and it goes slides into one of our robots cells, and robot does a visual inspection, whatever, or does the welding or soldering, screwing screws in or whatever tightening and then presents it back to the operator. And at that point, it's done. And all they have to do at that point is pack it out. So these smart packout systems can do a lot of things. They can communicate actively with the operator right there on the floor. So they can have multiple part bins or pick bins, we call that. There's plenty of technology out there, a lot of that we sell - we don't make manufacture but we resell from partners that we represent - that allows indication. So if we have multiple bins, and we scan it in, and that's a bit - some people call that IoT. It can be tied into the PLC or we do Red L:ion HMIs, and we do a lot of recipe based systems with Red Lion HMIs that does the same thing. So when you scan in your part, or your not your part but your your traveler, your router, your your part changeover card, or whatever that says I'm running this part now usually we scan that in, I guess you could select it.
Beth Elliott 22:49
Okay. On the HMI?
Brandon Ellis 22:51
Yeah, this is the part that I'm running or something well, that would tell us Okay, these are the pieces and parts that need to go in.
Beth Elliott 22:56
Okay.
Brandon Ellis 22:57
Well now with the PLC, we can illuminate you know, grab this one flashlight, whatever will direct the operator to grab from this band, but don't grab from this other bin. And then we also have sensors - pick sensors that if they happen to grab from the wrong bin, we can
Beth Elliott 23:12
Alert 'em. Shock 'em. Oh, I guess not.
Brandon Ellis 23:16
No, we we are not going to shock anyone whether they need it or not. No alert them in some way. So maybe we shock them through a buzzer. But yeah, a light indication of visual indication or sound an audible something like that is according to you know the customer as to how much of how great the sin is if you reach in the wrong bin. So maybe you have to have someone a supervisor come over there and reset the machine.
Beth Elliott 23:45
Oh, okay.
Brandon Ellis 23:46
See what you did. And the idea is to have a training moment or something a learning moment, teaching moment, that kind of thing. But nevertheless, you can have these the pick bins can be set up to where from a recipe standpoint, you can grab certain parts, again, sensors to put it together or maybe a vision system to inspect it. We do Datalogic vision systems like they're going out of style. They're great. Awesome, and they don't cost as much as the other guys. But anyway, there's plenty of vision systems out there. But But something is going to usually check to make sure that everything is as you say it is - that you didn't just pick the part and throw it in the floor. That you actually put it in place where it's supposed to be. And so we do this as part of quality checks. And when once that's all done, then you're allowed to pack it out and so packing out means putting it into the box sometimes it's according we've had situations where it's a whole pallet or tote pallet size tote that you're reaching through some type of a scanner or pic sensor large pic sensor or something. So if we see the operator reach through, we know that they placed it in the box.
Beth Elliott 24:44
Is there a weight on that?
Brandon Ellis 24:46
We can do weigh scale based systems. What you're right. Where we're checking to make sure they didn't just break the light. That they actually left a part behind. Or they didn't leave two parts behind. Or they didn't leave negative one part. So we want to make sure they're not reaching in and pulling out, we want to make sure they're not reaching in and placing more than one or more than whatever the quantity is supposed to be. And we can do that sometimes by weight -sometimes. Now weigh scales are there, they're a bit of a of a challenge at times, because you need to have product that weighs consistently, if you're doing a weigh scale system.
Beth Elliott 25:20
We can talk about that later.
Brandon Ellis 25:21
Yeah, so we will talk about that later. All right, so But nevertheless, that that that's an intelligent, or we call intelligent or smart packout - our packout assembly system. Assembly, meaning you're doing some amount of assembly, before you pack it out. In a pack out system, meaning that you're controlling the pack out to make sure they put in the quantity that they need to have the box. And that's a big deal for so I'll just hone in on automotive, we do a lot of tier one automotive and general automotive type work. In the automotive industry, if you're a Ford, or GM, or a Honda or Toyota, or whomever, and you've got a line, usually what they do is they if if you're running, if you're having a planing on 50 cars coming down the line today, then you'll set out enough materials for 50 vehicles. And so if if every vehicle gets one and you should have 50 in a box, and if it gets to you should have 100, and so on, so forth. And so when the fifth vehicle comes through, and is done, the box should be empty. If the box is empty, when after the 49th vehicle, that's a bad day. But if the box is in is full, or still has a piece or pieces in it after the 50th vehicle, my understanding is is that's a really bad day, because now they have to assume they missed one.
Beth Elliott 26:32
Yeah.
Brandon Ellis 26:32
And so there's all kinds of things that trickle down to the suppliers from that point of view. And from that point, and so these smart assembly packout systems help with that. We're verifying as best as we can, we're verifying quantity or verifying that the number of pieces that's in the box are consistent or correct. And there's a number of ways to do that with vision systems, with weight, with pics, sensors with things of that nature. And so that's a that's a smart packout system. And then if you're going to combine that which we typically see that folks do, they combine that with a certain level of assembly, or maybe even just quality check, to say all the pieces and parts and everything, this is a good assembly, and then at that point, it's backed out. And so again, I haven't mentioned traceability at this point, I haven't mentioned scanning apart or anything. The only thing that's recipe or part based, it's not even really part based, but it's it's recipe based is say that we're running part number XYZ. And we know that there's multiple pick bins, and XYZ gets these parts, but not the others, and monitoring which parts are being picked.
Beth Elliott 26:43
Okay. And you had alluded to the hand or the weighing. So do you want to talk about the material handle handling and management system?
Brandon Ellis 27:43
Sure. First, I just want to point out that I'm not the only one that talks with my hands.
Beth Elliott 27:48
I know, I'm sorry, that was me.
Brandon Ellis 27:51
So she she's guilty. So that said the Hand Weigh - with Hand Weighing is Yeah, it's I alluded to that earlier as far as weigh scales.
Beth Elliott 28:00
This is like an ingredient management type system.
Brandon Ellis 28:03
And that's our next category - material handling and management. And so smart packout systems kind of derived from IoT based systems with traceability they - IoT based systems just run through a summary here where we've been. IoT based systems for the example that we had and what the customer was thankful for was that we had a means gave them an affordable and easy means of creating this traceability so that they could could advance the product, minimize outflow or maximize their their their defect flow out prevention steps to make sure that if a part is being made bad we can arrest it mid process instead of end process. And then at the end ERP integration we we can add that to finish goods inventory, remove it from raw materials, do all the adjustments automatically and real time in that regard. And so that helped them get a really handle a good idea of their systems are where things are going and automate their system.
Beth Elliott 28:56
And they didn't have to wait week or day find out how many raw materials they need to order. Okay, okay.
Brandon Ellis 29:02
Well, I think the most important thing was they didn't have to deal with - we've got this huge order, the trucks waiting and an ingredient or part or something that we need isn't here - we're out.
Beth Elliott 29:14
Oh, that's terrible.
Brandon Ellis 29:15
Yeah, we're out of that. And so it's, you know, the dollar holding up a donut kind of thing. But, but anyway, and then the smart assembly packout systems is kind of a derivative of that in my mind, because it is a final assembly type step, but it's usually a smaller one process step. It may include assembly or quality checks, may even be having an automated aspect, but when it's done, we're gonna pack that out. And so it's more controlling the process and managing the quantity on a local level and local meaning right there at the at the point of process.
Beth Elliott 29:47
At that one process?
Brandon Ellis 29:49
Of course, if you want to integrate that in with the upstairs systems and bring about an IoT portion of that we can do that. It's just that in this situation, the customer was thankful that he did He needed to provide this type of system to satisfy his requirements by his customer and the people he supply to make sure his counts were right without doing a big elaborate system, things of that nature. In this case, smaller company didn't have necessarily all the the servers in place and all that kind of stuff to do historical base things, ERP systems, that kind of stuff, just not really where they are. So this is the type of system we gave to them. And but we did it in such a way that we're working with them. And one day, when they do go to the full on system, and they do need the full IoT integration, all these systems work with it.
Beth Elliott 30:39
Okay, that's nice. So they can kind of step up.
Brandon Ellis 30:43
That's right.
Beth Elliott 30:43
Okay.
Brandon Ellis 30:44
Because that makes the most sense.
Beth Elliott 30:45
It does.
Brandon Ellis 30:47
Material handling and management, though. So material handling and management. To me, material handling is more of a manual management. The final category we're getting ready to close with is automated automatic material management. So an automated material handling versus just a manual material handling. So the Smart Packout, I just said was more manual. It's controlling, kind of controlling the operator, pick these parts, don't pick those parts. Well, in this scenario, we were handling ingredients,
Beth Elliott 31:13
okay.
Brandon Ellis 31:14
And we're not automatically managing the ingredients, we're managing the system that holds the ingredients.
Beth Elliott 31:21
Okay,
Brandon Ellis 31:22
so there's step one, you've got to add the ingredients to your holding mechanism. So there was a what we call a refill portion. So what this was, was there was there was compartments that were locked. We could control them automatically locked, the locks on the doors. They the materials and ingredients could be loaded inside. And then there was indication at each one of these. And there was somewhere between 18 and 20 of these
Beth Elliott 31:46
Sensors?
Brandon Ellis 31:47
Well, the sensors but also the the container
Beth Elliott 31:49
Compartment?
Brandon Ellis 31:50
Compartments. Yes, thank you. And each one is locked. And so one central station, they all surrounded one central station, and at that station, there was an HMI. That's also where the central PLC was. There was a scanner, cordless scanner, I'll tell you why was cordless in a minute. And and there was a weigh scale. So this one was a weigh based system. Like I said, not trying to give away, no spoilers here, we're talking about ingredients.
Beth Elliott 32:14
Give a weigh.
Brandon Ellis 32:15
Yeah. So the refill starts first. And that is we put the ingredients, load it into the system. And so in that mode, we're looking for them to take the raw materials, scan the QR, the, the barcode on the raw material, we know that raw material supposed to go into this compartment and not any of the other compartments. And so we would unlock that compartment indicate that it was unlocked direct the operator - the associate to load into that. We're monitoring the absence/presence of the totes that they're loading with the chemical. We're not measuring weight. It's manual management, for the most part. So we're assuming and with manual, we assume that they actually what they scan they actually put in. So there is a training aspect, in that, that if they scan this, and what they're scanning is a it's a 20 pound bag, or a 50 pound bag, or 100 pound bag of goods, that that's what it's going to be. Now we weren't really keeping up with that, that was a thing we discussed doing. But we, we set it up so that when they wanted to do that we could. Because we know if we add 100 pound bag, we've got 100 pounds there. And this will make sense in a minute, we know when it goes away, or at least when it gets low enough to say
Beth Elliott 33:26
Need more
Brandon Ellis 33:27
You might need more. And so that's the refill process for each of the compartments. The reason the scanner was cordless is because this was these compartments where these were large totes. So it was a big area - bigger area. So you weren't going to take a curly cord, that connected scanner, corded scanner and get out there. So we had this cordless scanner. And so it would go out there - they could carry it with them and do their stuff. They also had a we actually fashioned a cart for them that they could raise and lower based on the tote.
Beth Elliott 33:55
Nice.
Brandon Ellis 33:56
So the scanner would go with cart. And so they would scan this is this is the stuff and it would unlock it and indicate and they would open the door and slide it on in, raise it a little bit, slide on in, lower back down whatever, close the door. We monitored the opening and closing of the door. We would relatch the lock and they would go do that through the refill process. So that's the refill. Then now you have the actual running cycle. So now we've got chemical or chemicals, ingredients, whatever in each one of the things. And so they now scan traveler, the router, the part number whatever they do to say this is the part we want to make. And so that leads to a recipe.
Beth Elliott 34:33
Recipe, okay,
Brandon Ellis 34:34
And so from the PLC standpoint, we know which ingredients are involved in in fulfilling that recipe - just like making a cake. And so we would then indicate green flashing i think is what it was whichever chemical or ingredient they needed to come get first and unlock the door. They would go get it on their, their little cart, bring it up to a central system where the weigh scale system was. Now, on the HMI we're saying okay, of this ingredient there's a visual indication it's empty. So the line is down low at zero. But this is the green area where you need to be. And so they will begin to load, manually load this chemical in, I'm saying chemical, it was an ingredient. We're loading this in, and it gets up into that space. And now we visually indicate, okay, you're good, you're where you need to be. And they would finish that up and return it. Once it returns, we're waiting for it to return. And then we move to the next ingredient, and turn that on, and so on and so forth. And so we would manage - help them manage the the just like the pick bins, right? It's real similar.
Beth Elliott 35:04
But this is ingredients.
Brandon Ellis 35:35
But then we're also measuring it at the end. So when I said it's 100 pound bag, we know assuming they don't spill any on the floor, throw some away before it's done, or whatever we know where it is. Now, that's also assuming - and this is the reason we didn't get quite into it all the way was because they didn't really need it, they liked it, they wanted to build a foundation for it. But there was not a step in their training and their process for partial bags and things of that nature. So now all of a sudden, you have to have a weigh scale to really do it right to say this is exactly how many pounds I'm adding if I'm not adding full bags only. And they had situations where they might add partials and that kind of thing. And so we just decided to hold off on it and just leave the functionality there and go from there. But but that's certainly a possibility. Now the cool thing is what made that all possible, even though we weren't necessarily doing an upstairs ERP system is all being controlled with our IIoTA based system. So the recipes and everything were residing on the database itself. And so in that,
Beth Elliott 36:35
Well yeah, because if a change comes down from the upstairs, they can take it and send it down to the to the weigh the weigh station and tell them you need to adjust your ingredient levels.
Brandon Ellis 36:48
Manage all your recipes from there.
Beth Elliott 36:49
Okay
Brandon Ellis 36:48
The other thing that it would do is it checks to say are you supposed to be making this. This thing that you're scanning and saying I want to make this you know, let's just use an example if we were a bakery, and we're making seasonal stuff?
Beth Elliott 37:07
Pumpkin spice
Brandon Ellis 37:08
Yeah, so last week was let's say Halloween but now it's not Halloween it's almost Thanksgiving you need to be making the turkey flavored doughnuts whatever
Beth Elliott 37:20
Yummy
Brandon Ellis 37:21
Yeah, ham flavored. Though I'll tell you I had a
Beth Elliott 37:24
You know ham and with pineapple on top of a doughnut might not be bad.
Brandon Ellis 37:28
You lost me with the pineapple. I'm gonna I'm gonna shamelessly plug a local business I hope I'm saying it right. Is it Sinas?
Beth Elliott 37:38
It's Sinas in Halls
Brandon Ellis 37:40
In Halls
Beth Elliott 37:40
Tennessee
Brandon Ellis 37:41
Yeah, now hold on a second. Halls Fountain City. There's a Halls Tennessee middle.
Beth Elliott 37:47
West Tennessee out near Ripley.
Brandon Ellis 37:49
Yeah. And they're there their Halls officially we're Halls Fountain City but anyway outside of Knoxville. Sinas doughnuts. If you haven't checked them out their fantastic. They get great burgers too. But they have it's a it's a maple iced doughnut with bacon. And I definitely I like bacon. I like maple iced. I would not have thought about putting those two together. Now my wife would have but I don't until it's done for you, and put on a plate in front of you. And then I'm like pretty much any guy I'll eat it you know if it looks alright. And so I tried it, it was fantastic that I guess the salt. She was
Beth Elliott 38:25
The sweet and salty.
Brandon Ellis 38:27
She talks about the sweet and salty and all that kind of stuff. So anyway, so if we're making a turkey flavored donut, that's what we're supposed to make. But you scanned the Halloween mix,
Beth Elliott 38:37
Candy, candy corn
Brandon Ellis 38:39
Whatever, candy corn flavor, then the upstairs system could say no, no, no, that was last week. This is not this week, you've gotten an old recipe or something. We don't want to waste ingredients on making Halloween stuff because that that that's not here. So that's the type of stuff that this system was able to do. And so that's but that's material handling and management. So we're managing the materials from the refill of the components to how they select them, but it's a manual process. Okay. So there's really nothing automatic about it. There are they they actually had gotten quotes for this particular customer thinking about the quotes that they had been given - everybody wanted to do a full on augers and batch mixing and, you know, all this big thing. But this this in their case really was kind of like the seasonal type stuff. They they did their batches,
Beth Elliott 39:30
Small batch?
Brandon Ellis 39:31
Small batch type stuff. Yeah. And quite honestly, this month, it might be this set of ingredients, but next month, they may actually remove this ingredient and add this ingredient and have a whole new palette of things that they can can make. And so this gave them the ability to do that at a reduced budget. It still had the manual aspect, but they did it wasn't like this was a 24 hour a day, seven day a week type production. I think they did their mixing like once, I'm sorry not once but twice or three times a week at the peak
Beth Elliott 40:04
So, automating it wouldn't make sense for them?
Brandon Ellis 40:08
That's right. And I think I said at the last podcast, some solutions are fantastic. But for other people, they make no sense at all. And so if you if you don't need this full on automatic thing, then don't buy it. But you have to have an option. And they we gave them an option. And for that they were thankful. And the fact that it worked great.
Beth Elliott 40:27
Yeah. And they can scale it up as well.
Brandon Ellis 40:29
Right. Well, I'm always try to instill into the minds of our designers and our programmers, we partner very well with people, we focus on the partnership and the relationship, because the way we see it the way I see it, they are experts at what they do. And their manufacturing, they know, I'm not going to know more than they know about the part that they're making. What I know what our people know is how to make motors turn, how to make conveyors move, PLCs do what they do, robots work, and in this case, data move, and those kind of things. And so putting those pieces and parts together with their expertise is how we empower them.
Beth Elliott 41:09
So you're working as a team.
Brandon Ellis 41:11
That's right. And so we are interested in the project. But we're also interested in the vision. What would help from kind of from a consulting standpoint, what do you need right now? Why is that important right now? And how does that affect a year from now, three years from now, five years from now. Because if we can say, Well, if you're wanting to get there in three years, let us go ahead and put this architecture together for you here, or at least leave a slot for it. And we're going to keep that in mind as we're growing on other projects, working with them on other projects. And then one day, when it's time to flip the switch, we flip it and remember, a lot of companies claim to do that kind of stuff, manufacturers, machine builders, integrators, whatever. But if there's always a statute of limitations, and there has to be a statute of limitations to a point, but remember, the product we manufacture still supports PLCs from the late 80s, or whenever, whenever PLC twos went out, and fives came in, I mean, that was a long time ago. So we try to always stay looking back. Because, again, from manufacturing standpoint, again, one of the things resounds with me, I'm so thankful that you all gave us an opportunity to reuse the equipment we had, because otherwise, we could not have realized what we've got here. Because we had this this older equipment, we really needed to bring it online, it was good equipment, it just wouldn't come online. And we gave them the ability to do that without where everybody else was saying, you're gonna have to buy new equipment for all these lines and all these lines and all these lines. And we're like, No, you don't need to do that. And so those cost saving measures make things possible. What's next?
Beth Elliott 42:46
Do you want to talk about an automated material handling? No, this is automated robotic handling, automated automated process,
Brandon Ellis 42:54
Automated robotic handling. So yeah, we can be short on this, because it's really what we just talked about with material management, so to speak, and with smart packout systems, and with final assembly systems, except it's totally automated. So this means you dump in all your stuff in one side widgets, pump out the other, the other end ready to go or maybe even in the boxes already. So automated robot handling. And that that's that's what we always say, but that's not really the case. There's always intermediate processes in there. There's always going to be a place for people and for jobs. And it's not about trying to eliminate jobs but helping them do their jobs better. And so in this case, that's what we were doing. So we had a situation where it was a labor intensive situation. There's there's four reasons to automate. This is Brandology, okay?
Beth Elliott 43:42
Oh, we're going to coin that term Brandology.
Brandon Ellis 43:44
Yea, some people may not agree with my Brandology. But in my 20 some years this is what I break it down to and this is different from the the three choices that you have when you're when you're buying anything or getting anything you can good, quick or cheap and you have to choose two. That's what they always said you can't get all three, good quality, quick turn around, and a cheap price. You can't get all three of those together. Gotta choose two. But this is different from that. Four reasons why I think that anybody should want to automate a process and honestly, if it doesn't fall within this, I don't know why you're doing it.
Beth Elliott 44:22
Okay.
Brandon Ellis 44:24
Number one quality so if you're wanting to increase the quality of goods. So so basically whatever you're doing, whatever your process is, if a human's doing it, they can't meet the quality standards or do as good a job or consistent the consistency standard standards and things that you want. We all get to that point. You can you can cut a straight line with with a jigsaw or a bandsaw. But, you know, a CNC router will beat you or a waterjet in straightness, you know, those kind of things.
Beth Elliott 44:54
Consistently, yeah.
Brandon Ellis 44:55
But a jigsaw costs $39.99 you know, down here at the hardware store and a waterjet costs $300,000, you know, so so
Beth Elliott 45:03
You've got to weigh you're
Brandon Ellis 45:05
Weigh it. Why? Why are you doing it? So so quality or consistency. So if you need to, if you're trying to do a process, you need it repeatable, you need it consistent, that's where an automation system may come into play. The second thing is if you want to decrease your cycle time, so sometimes, a robot usually robots are faster and more consistent, but faster than humans. Now, it doesn't always make sense to put a robot on everything we talked about that sometimes robots don't make sense. And especially when it comes to decrease cycle time, because we get to a point where the robot you're on because it has limitations on how fast it can move because at the end of the day it's a mechanical system. And so, so number, so that's it. So decrease cycle time. And in order to increase production, those are the same things. And then labor. What's that?
Beth Elliott 45:50
I was gonna say more parts per minute.
Brandon Ellis 45:51
More parts per minute. That's right, so increases in your production. Sometimes you don't even have to be faster for that. Sometimes you just if it's tiring, like an ergonomic or repetitive type deal. Automating that means that person has to take a break for a specific process. But a robot can go on theoretically forever. And so you can increase your production, your parts per minute, just by taking away the need for more breaks, because we have to do that for humans, because we don't want to wear out our our employees. Especially for certain repetitive tasks. And then the next thing is, is this is the one that we wants to talk about labor reduction. And so this is, this is where I don't see it as labor reduction with automation robots, I see it as repurposing of labor. There's always going to be a spot a place for, you know, standard labor. But there's definitely going to be a spot for what we call maintenance troubleshooter level and those kind of things with automated systems. So we're inventing those jobs - creating more and more of those jobs and job creation by adding automation. We may be eliminating a person from that specific process. But if we do that in such a way as to also try to increase production and things of that nature, you're going to need them in another place. So that that really is the reality. Robots - there's a lot of conspiracy out there about robots replace people and all this kind of stuff. Even the collaborative robots who are called the true people replacers, don't - we're finding they don't - you, you can't equal a person. We just aren't there yet. I don't know that we ever will be in my lifetime, because it's hard to turn to completely replace a person in every aspect of manufacturing.
Beth Elliott 47:34
Well, somebody's got to maintain the robot.
Brandon Ellis 47:37
Maintain them.
Beth Elliott 47:38
Program
Brandon Ellis 47:39
Feed them. We talked about a feeder system.
Beth Elliott 47:41
That's right, upstream - downstream.
Brandon Ellis 47:42
If you don't, you know, material management, you know, as far as the material handlers and that kind of stuff, loading the parts in. You just don't have many factories - there years ago, there was a term for what we call a dark factory, which means there's nobody there. Trucks come in, they dump truck something some kind of image, raw materials in one side, and then they're popping out on the other side. And there's minimal people inside. In fact, they don't even need lights. So they're referred to it as that's I've never seen that. That was something we talked about years ago, and I've never seen it come to come to be. But a dark factory usually means it's closed.
Beth Elliott 48:11
That's what I would think.
Brandon Ellis 48:21
Yeah. But that's what we're that was the movement back then was we're gonna automate everything and robots and all this stuff. And we won't, we won't need anybody to do anything. And that's just proven to be totally not the case. And, in fact, me just just really, what seems like a miniscule operation by a human could be nearly impossible with a robot.
Beth Elliott 48:41
Such as - a miniscule operation?
Brandon Ellis 48:44
Well, we have a situation right now with a customer that is loading and unloading, I'll say steel rods, from from a process. Sometimes that steel rod where they're unloading it from the holder, sometimes they have to - wish you could see me do this. What I'm going to do is I'm going to jiggle my fist a little bit, my wrist. They just have to jiggle it or maybe even roll it and jiggle it a little bit. Just to kind of work it out - just to get it to pop out. You can't teach a robot to jiggle the robot jiggle. You can't - you can try and I've watched with with glee a couple of times where people have tried and it's it's it's inspiring what they've done. But just that human element to be able to say it's not coming out stuck, I'm just gonna give it a twist and a little bit of a shake and pop it on out. That is very difficult to automate.
Beth Elliott 49:39
What about like artificial intelligence and machine learning? Do you think it get to that point where you could teach it to jig?
Brandon Ellis 49:46
I have a feeling what usually happens in those situations is you see half the call it laying on the floor and the parts destroyed and and you know, it bent it, then it's trying to shove it into the hole that it goes in or something and
Beth Elliott 49:58
disaster
Brandon Ellis 49:59
Ripping everything up. But but that type of thing is my example of a miniscule thing that you are going to spend a lot of time, money, effort and probably fail at the end to try and automate such a miniscule thing. The number of fourth, fourth, fourth reason. So labor reduction was number number three. And the fourth reason
Beth Elliott 50:18
To automate
Brandon Ellis 50:19
To automate is flexibility. And so, a lot of times when we're doing automation, especially, we have robots there to change over from one part, to the next, to the next is is not necessarily something as complex as tooling changes or, or things of that nature. We can actually just call different programs, as long as we're doing a similar type situation. If we're, if we're dispensing glue, or some type of sealant or something like that, as long as the the part is within the same work envelope a changeover, the flexibility is, okay, we're dispensing this shape now. But you scan a new party in or pick a new part recipe, and now we can do another one. And so those types, that type of flexibility to be able to change things. So those are kind of my four reasons of why you want to automate. Usually you can't pick all four. You may benefit across all four, but your goal needs to be one or two of those. So you may want to have flexibility and increase consistency or have flexibility and reduce labor, or, or something along those lines, decrease cycle time, while keeping consistency. But some of those I feel like are in conflict. You can't decrease cycle time, usually and increase flexibility, because it's according to how much you want to decrease your cycle time, if you're wanting a large decrease of cycles. And let's say I want to cut my cycle time, you know, by two thirds, so a 60%, or 50, even a 50% decrease in cycle time, we're gonna have to have mechanical system, we're assuming that's moving fast. It's according to what's your cycle time is. If your cycle time was already hours, maybe that's not that big a deal. Unless, you know, we're trying to dry and paint will only dry at a certain certain certain rate. But if you're moving parts, we're talking about material handling, for the most part in this, this podcast, physics comes into play. I mean, you've got mass times acceleration, force equals mass times acceleration, all these kind of things, Newton's laws, they all exist, we can't do anything about them. And so now all of a sudden, a robot may not be able to physically move that fast with the mass of part that you're moving. So if it's a light part, we can do that. But now all of a sudden, you stick a heavy part in there for the flexibility option, you're gonna have to slow it down. Or if it's going to be the heavy part, it needs to become more focused, more laser beamed. Maybe we do linear motors, maybe we do, you know, more dedicated systems to move that type stuff if cycle time is your goal. But don't choose cycle time if it's not really your goal. If your goal is to reduce labor and add flexibility, then cycle time needs to be what it is. If it gets a little better, great. You don't want it to get worse, certainly, but you should not want it to get worse. Unless you're running a product on the flexibility side of things that you wouldn't normally run, maybe it just takes longer to run that product. But whatever that product is your worst product case, they should stay with what you've got, you should that's fair to aspire for that but aspiring to say I'm going to knock my cycle time in half and reduce labor and keep my quality
Beth Elliott 51:14
And have flexibility
Brandon Ellis 52:44
And have flexibility. You know
Beth Elliott 53:19
And, I want it cheap.
Brandon Ellis 53:22
Yeah, you just can't, you can't stack up too many of those as your primary goals. So getting back to this automated robotic handler, that's kind of what we did there. So we had an automatic feeder that we designed up that would feed parts to the robot consistently. That's important because the robot needs to grab them consistently. You can get in now into 3d vision systems that can - the robot can decide where it is on a stack of parts and go in and pick it and that kind of stuff. But we're trying to keep cost down on this particular one. So we're running a known shape of parts. It's coming through, it's being presented, the robot grabs it. In this case, it was a collaborative robot, but it was guarded.
Beth Elliott 53:57
You've never seen an unguarded collaborative
Brandon Ellis 53:59
It was guarded because it had a safety scanner on it. That would grab the piece. And there was a piece of equipment that was a manual process and what they wanted to do - it was a so manual process. It was a repetitive type deal. So that falls under quality, the
Beth Elliott 54:17
The repetitive. Yes.
Brandon Ellis 54:19
Yeah, so, so consistency. The other thing that they did was they of course, reduced, reduced it by an operator, they didn't really reduce it by an operator because that operator was now able to manage multiples, because the operators job instead of running this repetitive thing that was making their hand hurt all day, they were loading the magazines. And so now their material handling in a safe and you know, easier way for them, and the robots are just running. And so they're getting the consistency of what they need. Then the robot would actually also presented to a Datalogic vision system to do a final quality inspection, visual inspection from there, and they would either reject it or put it into the, to the good box, and that was the main packout .And so those are small level small, small level automatic robot handling systems in that particular situation, they were needing consistency. And it was a repetitive ergonomic type deal. But they didn't have a good way to do that. So we helped them engineer the automatic feeder, put the robot in place, and then use the piece of equipment they already had. The piece of equipment worked fine. They had already established an ROI on that piece of equipment. The problem was, they were getting in consistencies - defects were being caused by inconsistent introduction of the parts to there. And then and the reason it was inconsistent is because the operator was hurting.
Beth Elliott 55:37
Well, yeah, if they're keep on doing the same thing over and over again.
Brandon Ellis 55:40
And so it was a tiring and, and hurt ergonomically draining application. And so they were they were happy because they got the consistency they wanted, they actually increased their cycle time because there wasn't because they were having to take a lot of breaks just just for being worn out.
Beth Elliott 55:57
Yeah. And in that person probably has a much more fulfilling job now.
Brandon Ellis 56:02
Well, that Yeah, absolutely. I you know, I talked to a couple of them and, and the workers and the comments that I got was, and I'm so glad I don't have to do that anymore. So hey, we're thankful.
Beth Elliott 56:14
We are thankful. That's all the projects that I had on our list here. And I think we're running up on time.
Brandon Ellis 56:21
We're over an hour. Guys, I apologize. But Happy Thanksgiving. I want to do a quick shout out to the Red Nation Robotics Team, Team 4576. They won it all last year, and were getting ready to go to the world worlds - can I get that out - and COVID knocked that opportunity out. So we support you guys and we want to keep doing that. So wish you guys the best.
Beth Elliott 56:43
And I am thankful for our listeners for keeping on downloading and sharing and I just want to say rate, review and subscribe. Rate our podcast and do a review and subscribe and when when you start rating and reviewing, it'll start popping up closer to the top so other people can discover us.
Brandon Ellis 57:05
Rating and Reviewing. Guys listen, have a fantastic and safe and healthy Thanksgiving. And we will see you - hear you - listen let you listen to us, I guess in two weeks.
Beth Elliott 57:16
All right. Happy Thanksgiving, Brandon.
Brandon Ellis 57:18
Happy Thanksgiving, Beth. See you guys.
Transcribed by https://otter.ai
