Industrial Automation - It Doesn't Have To... Be Menial

Menial tasks are those repetitive, tedious, or dangerous tasks that a robot is capable of doing freeing up time for associates to focus on high-value-added tasks.

The types of robots used to automate applications can be different and sometimes confusing, so we're breaking it all down for in this episode.

Please join us as we explore collaborative robots, also called cobots.  You'll hear the differences between an industrial robot and a collaborative robot.  As well as:

• What makes a cobot collaborative  
  
  
• Are there cost savings between an industrial robot and a cobot
  
  
• The types of applications that are better suited for collaborative robots
  
  
• How collaborative robots can be used to empower employees
  
  
• The ROI (return on investment) for a cobot

Did you hear?  elliTek has partnered with Hanwha Robotics to provide United States manufacturers their HCR Advanced Series collaborative robots!  Take a look at these sleek cobots.

Reach out to us with any questions or future topics!

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If you don't want to click on those links, pick up the phone to call us at (865) 409-1555 ext. 804.

Transcript

Brandon Ellis  0:26  

Hello, everybody, this is Brandon Ellis with elliTek and "Industrial Automation - It Doesn't Have To...". And I'm sitting here across the table with my co-host, our marketing manager, Miss Beth Elliott.

Beth Elliott  0:37  

Good morning, Brandon. Good afternoon, everybody. Good day.

Brandon Ellis  0:42  

We never know what time they're gonna listen to this. So good day or night. It is morning. We're sitting here doing our podcasting session. And it's a beautiful day out. It's actually Friday at this moment. And so, we're looking forward to a rainy weekend. 

Beth Elliott  0:56  

I know, I know. It's so beautiful today. I wish we had a window in here.

Brandon Ellis  1:01  

So, thanks for joining us today. Today we're going to be talking about a bit of a takeaway from our last podcast, at least the last half, which was the last podcast was "Industrial Automation - It Doesn't Have To... Be Manual", which we focused on RPAs, RPA, another acronym, Robotic Process Automation. And so it has nothing to do with robots, industrial robots. But it is similar to because I have to get into my zone at some point. So, the Part B, side B of that of that podcast, we talked a bit about collaborative robots. And so that is something we're gonna expand on today. So today, season two, episode eight. Go ahead, Beth.

Beth Elliott  1:45  

"Industrial Automation - It Doesn't Have To... Be Menial".

Brandon Ellis  1:47  

Menial. And we discussed menial, really it has a focus on the jobs that a collaborative robot can do. And honestly allows for reclassification of people that are doing those, gives them more hours in the day, that kind of thing, even can make the job safer from an ergonomic standpoint. And so collaborative robots do this well, but we're also going to talk about things that they may not do that well. So we want to look at both sides of the coin on that. So that's what we're going to talk about today.

Beth Elliott  2:19  

Yeah, but before we get into that, there are a couple new employees at elliTek. 

Brandon Ellis  2:23  

That's right. 

Beth Elliott  2:23  

Yeah, it's growing. I tell you what the parking lot was almost full.

Brandon Ellis  2:27  

Yeah. We're gonna have to add on, which is a fantastic thing, considering the pandemic of 2020, and all the things we've gone through. I was reading today, this morning, actually, an article about how we're seeing companies opening back up, we're seeing people going back to work. And so that's great, great news. We're seeing travel. One of the airlines was announcing that they're hiring pilots again, which is fantastic. Unless you have to wait in line, if you've been enjoying. If you've been flying through this whole thing. You've probably enjoyed no lines and basically owning your airline, but I think that's going away now. So, as I guess the vaccines are going out that's affecting some folks. And then some of us actually went through it and earned our antibodies the hard way. But certainly, it's good to see that people are feeling more comfortable. And boy, it's 

Beth Elliott  3:23  

Starting to live again. 

Brandon Ellis  3:25  

It's a big departure from a year ago.

Beth Elliott  3:26  

Yes, absolutely. 

Brandon Ellis  3:28  

This time last year, things were really, really dicey.

Beth Elliott  3:32  

So who are our new employees?

Brandon Ellis  3:34  

So, let's talk about the new employees. Yes, we have two new employees. And so, I'll announce them based upon start dates. That way there's no favoritism. I'm very happy with both of them. Joe Polakiewicz is one of our, is a new mechanical designer, mechanical engineer. Joe got his degree from the University of Tennessee, Knoxville.

Beth Elliott  3:53  

Go VOLS. 

Brandon Ellis  3:54  

That's right. And he's got his degree in mechanical engineering, as well as aerospace engineering.

Beth Elliott  4:00  

Smart fella.

Brandon Ellis  4:00  

Yeah, he's he's, we're I've been really, really impressed with him and really glad to have him on board. And then Todd Ader. Todd has, is a senior fabricator. He's actually more than that. He's a machinist, and a fabricator. So he can weld, machine, assemble, make it happen. And Todd's been here just coming up on the end of a week and has already made a huge impact. So 

Beth Elliott  4:23  

He has.

Brandon Ellis  4:24  

As has Joe. And so that we're really happy about them being able just to jump in and hit the ground running so. So welcome, guys, if you're if you're listening to this podcast, Joe and Todd, thank you very much for your for coming and for being part of the team. 

Beth Elliott  4:38  

Absolutely. Absolutely. 

Brandon Ellis  4:40  

So, let's see. Nope. Here we go. Thanks for being part of the team. That's, that's applause. It kind of sounds like rain. 

Beth Elliott  4:50  

It does. But there is somebody yelling.

Brandon Ellis  4:52  

Somebody yells at the end.

Beth Elliott  4:53  

Yeah

Brandon Ellis  4:54  

Just like someone yelling in the rain. 

Beth Elliott  4:55  

Kinda

Brandon Ellis  4:55  

Anyway. So, there you go. 

Beth Elliott  4:59  

Alright

Brandon Ellis  4:59  

So, let's

Beth Elliott  5:00  

Do you want to get into the topic today? 

Brandon Ellis  5:02  

Go ahead. Let's take us there.

Beth Elliott  5:03  

So, before we go into the collaborative robots just briefly tell us what the difference is between industrial robots and collaborative robots. So, the audience has a kind of an understanding of that.

Brandon Ellis  5:15  

If anyone has seen, especially if you've seen commercials, videos, whatever, online of, of the car companies, so the large automakers, you see the big robots that are huge robots that are hanging on the sides, and they're coming down, and you see weld sparks popping off of the car bodies as they're coming down the assembly line. Those are industrial robots. So industrial robots get very large. And then they're also very, they're very much a focus on accuracy and speed. Also, the payloads can be fantastic. 

Beth Elliott  5:47  

They can carry some heavy stuff.

Brandon Ellis  5:49  

They can move car bodies around. And so it's all about just mechanical muscle in a very high speed and accurate way. We use them a lot of different ways. But there's also smaller arms, industrial arms that are still industrial. So what's the difference between that and a collaborative robot, I have seen situations where an industrial robot can be guarded, in a clever way, so it's OSHA compliant, using safety, light scanners and things of that nature. You have to use safety scanner pretty much to do it. But the front part can be mostly unguarded except guarded by light.

Beth Elliott  6:23  

Okay

Brandon Ellis  6:24  

But it's still industrial. And the difference is, an industrial robot has the mechanisms by which to protect itself, and potentially protect the end of arm tooling that it's using to do its job. But not to protect people. And so, the force sensors, it's it has, are much higher, much, it's more, they take more of an impact before they decide there's a problem,

Beth Elliott  6:47  

Okay. 

Brandon Ellis  6:48  

And so, the sensors that are in a collaborative robot, are force sensors that are more sensitive. And so, they're looking for they're there to protect people. Whereas an industrial robot has sensors that are there to protect tooling and protect itself. But that's, that's a higher grade, you're already damaged if you're a human. So industrial robots can be very dangerous, if not guarded correctly.

Beth Elliott  7:12  

Okay. Are there any other differences?

Brandon Ellis  7:15  

Well, again, it comes down to industrial robots, because they're moving fast, because they're moving accurately. And also, because their sensors have a higher level of compliancy. In other words, though, they'll deal with. Robots can shove through cardboard boxes and keep on going and industrial robots and not even think about it.

Beth Elliott  7:36  

Oh, a collaborative robot would not do that. 

Brandon Ellis  7:40  

Well, it has the sensors that should keep it from doing that. You can change the sensitivity of those sensors and make, we call it more or less collaborative, as far as the safety, but in the sensing, but you can't turn it completely off. So yes, collaborative robot would not necessarily punch through, you know

Beth Elliott  8:00  

A cardboard box. 

Brandon Ellis  8:01  

We actually had an application or a customer that was telling us about, they, they package parts. And so, the robots are just putting parts into cardboard boxes. And they're putting them in in a certain arrangement. And one of the boxes somehow got loaded upside down, or on its side or something. So, there was no opening for the robot, and it popped right through 

Beth Elliott  8:22  

It was gonna do its job, no matter what.

Brandon Ellis  8:24  

And dropped it in. Just kept putting holes in the side or the top, whatever, bottom of that box and just busted right on through. And, and you know, the comment was made that's why we don't use collaboratives, because we need to keep going. Because it was from a maintenance standpoint. We don't want downtime. So, a collaborative, of course, would have stopped and stopped the operation and somebody would have to call maintenance, that kind of thing. But so, and the reality is that's not a good application use application for a collaborative robot, in his case, I guess. But industrial robots are meant to be strong. And so that means the payloads are generally higher. Not always, it's according to the size. But you can get up to these, I mean, literally move car bodies around. And you're not really going to do that in a collaborative fashion. We talked about in the last podcast, and just to reiterate that analogy. We were all taught as children not to run with scissors, but nobody ever got onto us for running with the Kleenex tissue box. And so, it really comes down to how heavy and of course the scissors are not heavy, but they're sharp. So, all of your force is pinpointed on a single point. And so, all your pounds per square inch are going across a very, very small area, and so it will inflict damage. Whereas a Kleenex box doesn't have a lot of force in it as far as mass. And it's also wider and it'll absorb and that kind of stuff. So that's those are the things that come into play when you're doing your risk analysis from a safety standpoint for either industrial or collaborative robots. But between those two, you end up with a list of applications. That are really either good or bad for collaborative or good or bad for industrial. There's not much that industrial robot can't do that a collaborative can, except work closely with people and still not, I'm gonna say it. I've never seen a collaborative robot that's not guarded.

Beth Elliott  10:22  

Alright, take a drink everybody.

Brandon Ellis  10:24  

There ya go. So, you just don't stick a robot in by people and say, these force sensors are gonna be enough. I haven't met a safety coordinator or an OSHA Inspector, anybody that's willing to sign off their name to say, slide that robot in, don't do any additional guarding, and it's going to be fine. They all want some additional guards there, including the light base guarding, which is usually what they use, the safety scanners. And so safety scanners, of course, are always scanning, looking out, and coming back, it's time of flight on infrared laser light to see if something is coming into its space. And, and if it does, it can get, it can be set up programmed to where there's a warning, and then there can be set up and programmed where there's a, an emergency situation. On an industrial robot, you stop. On a collaborative robot, you get really slow or you stop. 

Beth Elliott  11:22  

Okay

Brandon Ellis  11:23  

So, you don't have to necessarily stop but you want to get down so slow, based upon what you're carrying. Get your speeds down. Again, you can walk with scissors. You can't run with scissors. Get your speeds down, get all that kind of stuff down. So that if a human comes into play, those sensors can pick up on it and arrest the motion in a safe way versus if it's moving very quickly.

Beth Elliott  11:48  

Now, is there a, is there a cost difference between the industrial robots and the collaborative robots? 

Brandon Ellis  11:55  

Well, I mean, if you're gonna, if you're, you mean, let's so let's kind of categorize them into where they both could be considered. You're not going to get a collaborative robot that's moving a car body or truck body around. So, let's compartmentalize all those large, really high payload.

Beth Elliott  12:10  

okay

Brandon Ellis  12:11  

So, in your smaller payloads, you can actually spend less on an industrial robot than a collaborative. Some of the industrial robots are, are very, very competitive cost wise. The cost on industrials have come down a long way. So what's the payoff? What's the difference? Why would you want to consider collaborative? Well, everybody, we talk about the safety part of it, but still, you're gonna have to, you're gonna have to guard because of OSHA guidelines, you're gonna have to guard the industrial a bit more. So, there's going to be hard guarding around certain things, you're definitely going to have safety scanners, you're not going to have an absence of safety. There's gonna end up being just because you know, 99% of the time, there's going to be some amount of hard guarding, some amount of safety scanners, potentially, some amount of light curtains, potentially, things of that nature. And again, it's according to the size. When we were when we were talking about in our episode, "Industrial Automation - It Doesn't Have To... Be Unsafe", we had Dave Rice with Datalogic on as a special guest. He was talking about the differences between light curtains and, and safety scanners with robot cells, but it also comes down to the size of the robot cell. Because if a person if it's a small, small robot, the person can't, may not be able to enter the space physically. You know, they just can't physically fit their body in there, then that can be handled in one way versus a large robot cell that's as large as a room to where you could actually be in there and not seen about the light curtains and things of that nature. So that's where the safety scanners come into play. But compartmentalizing all those to get down to where we are. You can spend less money on an industrial robot. Marketing folks, sales folks say, Yeah, but you make it back up with the guarding and all the safety. Can I say it again, everybody got their, their glass ready? I've never seen a collaborative robot that didn't involve some type of guarding. And so, you're going to spend that money anyway. So really, it comes down to, it does come down to ROI to a point. The other thing is that cobots have, collaborative robots have the industrial robots do not have is direct teach capability. That direct teaches is 100% possible because of those safety force sensors. It allows you to have the robot motors powered, but if you can reach up and grab the end of the robot, physically, the robot not using the pendant but grab the robot and you apply force, those sensors will pick it up. But when it's in that direct teach mode, it will give way. It'll move with you. So, it's kind of a floating posture, almost an anti-gravity posture. 

Beth Elliott  14:49  

Okay

Brandon Ellis  14:50  

Industrial robots can't do that. They don't have the sensors in there. And again, any of the torque sensing that they're doing, it's a much higher level of, equates to a much higher level of force. And so, if they did it, you would be really applying some force. And it wouldn't know the difference between, they're just not set up for that. It might not know the difference between I'm crashing or you're telling me to move somewhere. 

Beth Elliott  15:14  

Okay, okay

Brandon Ellis  15:15  

Cuz that's really what those are, is more for crash sensors, crash, crash detection, and direct teach is not a crash. I would like to see one day, an industrial robot company, add sensors, force sensors for direct teach, but still remain industrial. Because it, because of this fact that everyone loves the direct teach. Now, again, the sales and marketing people. And I tell our salespeople to not to, not to sell it this way. It's very easy for them to come in. And they'll do the direct teach and show you how you can go in and pick something up with their little, you know, desktop demo and things of that nature. And then they'll say, make this statement. And that's all you have to do; you can program it yourself. 

Beth Elliott  16:02  

That's not the case. 

Brandon Ellis  16:03  

It's not the case, because every robot has to have all of the what ifs, what, you know, all of the error, what we call error, error, error handling. So, if there is a crash, how do you recover from that? If, if you're in a certain posture, when something happens, how do you get out of that in a way that's safe - to the to the robot, safe to the equipment around there, safe to the people around there. So, if you're reaching in a hole, you may not want to go straight up, because you'll crash again. You have to know where you are and be able to do those recoveries. And so those kinds of things have to be thought through.

Beth Elliott  16:39  

Did they those get programmed beforehand? 

Brandon Ellis  16:42  

Yes. 

Beth Elliott  16:43  

Okay.

Brandon Ellis  16:43  

So, but the direct teach can be utilized, if you're a good programming company, like elliTek. If you're doing your job correctly. If you, if you're an integrator that's programming this, you can set it up to where paths are being utilized. But you still have to make sure that if I'm in a weird posture, and suddenly they change the path to where it's, it's odd, you know, there's there's a chance you can get it mess, messed up from the original process. So, you can call paths and allow users, end users to, to go in and just, you know, put it in a mode that says, okay, teach me what the path should be. And they do a path. But if they take a path is totally out of, out of whack, it could, it can mess up the next move that comes after that, or the recoveries that are related and that kind of stuff. So that that's why with us, we, we do training with our systems. We want to make sure that everybody knows, even if even if we've written, done the integration on it, and written the program so that these paths can be touched up, if you will, we want to make sure they understand what are the confines that works with the program. And if those confines need change, we need to modify the programs or things of that nature, or we work with them to do best practices on how to do that. But at the end of the day, direct teach is a much easier means. Grabbing the robot, moving it to a point and saying teach the point or grabbing the robot and moving it through a path and say this is how I would do it. Again, we're talking about primarily menial tasks is what we're shooting for. We'll talk about some of those classifications later. But sometimes those tasks also require finesse from the human point of view, and programming finesse 

Beth Elliott  18:30  

The wiggle jiggle

Brandon Ellis  18:31  

All that kind of. Yeah, it's a little it could actually be a little easier. Because just when we're talking about RPAs and how they record mouse clicks, and keyboard clicks, with direct teach, you can record those motions. And so, if the operator is able to actually be in a situation where they can grab the robot, move it in this direct teach mode in a fashion similar to what they would do. And then do the wiggle jiggle. It'll record the wiggle jiggle. Because it's recording all what they do. And then when you call it. It's gonna do it every time now. 

Beth Elliott  19:03  

Oh, but not every time it needs it. 

Brandon Ellis  19:04  

Right. So that's, that's where you've got to think in terms of, they're still not people. So, there's applications that make sense for collaboratives and there are applications that don't. There's applications that makes sense for industrial and there's applications that don't. But cost wise, you can get a. Because you're, you're having to pay some extra for all those force sensors. And so, you can get an industrial robot with the same payload, higher speed capabilities and accuracy. But it does have to be guarded. But you can get that for less sometimes than a collaborative solution.

Beth Elliott  19:40  

It all depends on the application, doesn't it? 

Brandon Ellis  19:42  

Yeah. And then the guarding may get you up there, but if it's significantly less, which sometimes they are, you can pay for, it doesn't take a whole lot to pay for guarding. So, it's kind of back and forth. But collaboratives have some unique things that you can do. It gets you thinking outside of the box that we normally think in in terms of programming and use. 

Beth Elliott  19:59  

Do you want to go over some of the applications? 

Brandon Ellis  20:08  

Absolutely. 

Beth Elliott  20:08  

So, I was looking through some and the one I thought would be interesting would be welding. Do you want to talk about how cobots are better at welding? Or maybe not? I don't know. 

Brandon Ellis  20:19  

Well, we there we've been doing industrial weld cells with industrial robots for years. You've heard me say that I think welding is the perfect, one of the among the perfect collaborative jobs. And welding but welding is different. But welding is a science. Welding is an art. And so, a good. Well, you can talk to Todd. A good and compare him to me. I mean, he's 1000 times better than I am. Both of us can say, yeah, we can weld. But you can tell the difference. You know, you look as well do you be like, that's fantastic. You look at mine, and it's like, golly, but I'm not a welder. Welding is a science. And so. And then you also have things like, we're talking about specifically MIG welding, most cases. But MIG welding, there's a wire that's driven out by a motor, a feed motor out of a weld head. That wire is electrified so that when it touches the part, which is grounded, or positively or negatively charged, it creates an electric arc. Well, that electric arc melts the wire and heats up the, of course the material, the metal that you're on there. And so, you have hopefully enough electricity to get a lot of heat on both the metal part and then of course, the wire's melting. And you get good penetration, and it blends the wire the melted wire with the surface of the melting metal, and it bonds. It creates a weld. And so, you have to do that while you're moving, typically, unless you're tack welding. I talked about the industrial robot, you know, the big car companies, the automakers and how they come down and just see one burst of sparks. So that's tack welding. It's just doing quick little weld; it’s not doing a continuous weld. 

Beth Elliott  20:36  

okay. 

Brandon Ellis  20:38  

So, tack welding is done a little differently than continuous welding. But the reason I say that I think that's a good collaborative one, especially if you're doing the same weld over and over in a fixtured environment. Most parts are fixtured, which we want the repeatability in any robot style, we want the repeatability. But a collaborative robot needs to do two things. It needs to move slowly and fairly accurately. It needs to have a light payload. Well, a MIG head is very fairly light on a weld head, and you don't weld fast, you have to weld fairly slow, relatively. So, it would fall, I think it would fall definitely below the safety concerns. So really, the only guarding you need is 

Beth Elliott  22:46  

For your eyes

Brandon Ellis  22:47  

Is for your eyes, yeah, the weld curtains or something like that, so that the arc flash doesn't, you know, get in people's eyes that are around. But you need that for any kind of welding, whether it's a person, industrial robot or anything. So, I've often said that I think welding would be a good collaborative application. But you have to combine that with your welder, and that's where the robot and the welder have to kind of work together. So, if the, for some reason the arc that you've created extinguishes, if it goes out, then you need to stop, especially if the wires still feeding, you need to stop the feed on the wire. It's according to what's going on, what's controlling that. So, there's, there's those kind of detectors that usually come in with the robotic welding equipment, those kind of things, that's still got to be there. But if you had a situation where, with the coming back to the direct teach, where you could have a person emulate what they normally do. Then recording that path could be doable from a collaborative standpoint. Again, the robot, the brand robot, that kind of thing, you got to make sure, from an electrical standpoint that, you know, it's grounded. That you don't have any like, all those with that weld current doesn't run through the robot and fry the controller or anything like that. So, you got to make sure. And then of course, I'm talking general here, the, the manufacturers need to have a say on whether or not they're, they want their collaborative robots in a welding application or not. Because again, there is electricity involved fairly good currents because you're creating an arc. And if it went through the wrong path to ground, it could be like a lightning strike. And so, you don't want to damage anything. But I've just I've just always thought that that would be a good one to do. Now, we haven't done personally elliTek hasn't done any collaborative based welding projects. But because of the speed primarily because of the speed and the direct teach, I just think it would lend itself to that.

Beth Elliott  24:43  

Because industrial robot you'd have to program.

Brandon Ellis  24:47  

Well, with industrials, you have, again coming into that whole dance between the robot and the weld system. You have height detection, so it's it automatically senses how high it is and feeds that back to the robot, if it needs to make corrections. You have the, of course the arc sense. You have all these different things that's going on to make sure that everything about the welder is operating correctly, that your heights correct. And then it's just about, you know, managing, you're managing your height and adjusting that, but you're also managing your rate, how fast you're going, and then your direction. Welding isn't just a straight move forward, typically. You really, if you watch a person weld, they're making like tiny circles or c shapes, I guess you would say. It's kind of, it kind of creates a wavy look. So, you're kind of moving forward and moving back, moving forward, moving back. So, whether or not you have the robot doing that really comes down to what you're doing in the application. It's a specialized thing, it's still going to be specialized. But I think from a collaborative standpoint, you could get away with less guarding. Because it's, of the collaborative sensors versus the industrial, which is gonna have to still have all the guards. Because, you know, it just has the capability to, to do some damage. Robots are not little safe, friendly things. I've been in situations and we take it very seriously in our shop, that even a small robot, small arm industrial robot will very quickly hurt you if you're not careful. And it's easy to get really comfortable with them. And so in, they need to be respected. They're fast, and they're powerful. And again, if they don't sense you as a, hitting a wall, and sensing the crash, then they'll blow right through you like the cardboard box. And so don't lacks on the safety portion with industrial robots, you have to have safety. Collaborative. Meh, it's up to the, to the safety coordinator.

Beth Elliott  26:57  

Risk Assessment

Brandon Ellis  26:58  

I just haven't met the safety coordinator that's willing to put their name on the line. 

Beth Elliott  27:01  

So, welding Can I was thinking we could talk about the industries per application, but it seems like some of them kind of mixed together. Do you want to do that? Or do you want to touch on

Brandon Ellis  27:08  

Some of them do and so welding is sort of like dispensing, but not really. You take out all the, you take out all the smart stuff that you have to do all the artwork of welding. Because welding is a science, I mean, it is but dispensing and gluing is not necessarily that scientific. You need to follow a path; you need to follow a certain velocity or rate. If you go too fast, it won't leave a bead or those kinds of things. It's according to how you're dispensing. If you're dispensing a continuous bead of glue, or silicone, or whatever you're putting on, epoxy, that kind of stuff. Or if you're spraying, sometimes it's spray more of a spraying application. Well dispensing glue and spraying glue, well, that's a lot like painting. So, paint comes into play. But paint, of course, is typically explosive. So collaborative robots, to my knowledge are not, don't meet the classifications to be in an explosive, explosion proof type environment. So maybe someone out there makes one. We certainly don't. We would not put one of our collaborative robots, you know, with a spray gun on the end spraying paint. It's just, it's just unsafe, and OSHA would not agree with it either. And neither would the manufacturers. That's not how it's meant to be used. But dispensing glue, as long as it's not, you know, highly flammable type of glue, media, things of that nature. If it's a fairly inert.

Beth Elliott  28:38  

Glue that goes on to like the envelope.

Brandon Ellis  28:44  

That or the stuff we've done in in automotive is, so engine components get you they put on some type of a gasket seal or something like that, sealant. And so, we would follow the edges of all the machined parts and dispense the glue. And then you know, the thing would, a part would be placed by an operator or something like that and moved on. So maybe it's going down a conveyor or something like that, but you can dispense. You can do that with industrial robots as well. But again, collaborative robots come down to, in my opinion, not so much about the lack of safety because it needs to still have full safety risk assessment. And safety will be required to a point, but it really comes down to the direct teach portion and being able to modify those paths or teach new points.

Beth Elliott  29:35  

Without having to program it.

Brandon Ellis  29:36  

Without having to grab a pendant. And because the pendant programming, it's not like it's that hard, but it does take class time to get to know it. And then if you don't do it often.

Beth Elliott  29:46  

You forget 

Brandon Ellis  29:47  

You forget how to do it. And then, of course a lot of these a lot of these companies have three different manufacturers of robots and so the each pendant is 

Beth Elliott  29:58  

Different. 

Brandon Ellis  29:59  

Specific to the robot and that kind of thing. But with collaboratives, they pretty much all have a direct teach capability. And it's just a matter of remembering how to get it into that mode and the right spot, and then you just grab it and go. So, if you're wanting to create a new part, path for, you know, something changed on the glue dispense. And now you don't need to go out to this point anymore. You need to change the path here. You can do that fairly easily without having to really be a programmer. You just, it's kind of what you see is what you get, you move it in the way that you want it to move. And then it'll, it'll follow suit. And so, I think that, then tied together with the fact that you can, you're going to, I think you're going to have guarding, but that guarding is not going to be as substantial as the industrial is. So again, doing the safety light scanner, and nothing else with a collaborative is certainly a possibility, as long as you're not impeded by anything to where somebody can get between it, the scanner and it, but if it does, the collaborative sensors, force sensors are still there. Again, you can turn that sensitivity way up so that it's not as sensitive or way down, I guess you'd say.

Beth Elliott  31:13  

So, it's adjustable?

Brandon Ellis  31:14  

It is adjustable, usually. In our robots, it's adjustable. Because sometimes, and this is where we certainly use the scanners, is if no one's in our proximity, we're going to act more industrial than collaborative, but we can adjust that level of sensitivity on the fly. So, if someone gets closer, we can slow down. But we can also turn the sensitivity up.

Beth Elliott  31:39  

Okay.

Brandon Ellis  31:40  

And we're okay, I'm going to plug it because I'm just excited about it. We are recently have been awarded a partnership, or we are in partnership with Hanwha Robotics. And with their arms, they're not the light aluminum-based arms that so many are. They're actually a cast arm. And they have the ability. And this is what I think if everyone's being honest, everyone wants, like I alluded to earlier, everyone wishes that there was an industrial, fully industrial robot, which means high speed, high accuracy, that had direct teach capability. So, you could safely do a direct teach, and then walk out, close the door on the guarding, and let it just scream. 

Beth Elliott  32:21  

Do its stuff.

Brandon Ellis  32:21  

Yeah. 

Beth Elliott  32:22  

Okay.

Brandon Ellis  32:22  

That's what, that's what I think everyone wants. And so, everyone tries to get that out of collaboratives that are on the market now. And what they're finding is, is the collaboratives not built for that because it's built so ultra-light. The HCR series from Hanwha is getting us very close to that. It's not an industrial robot. It's still a collaborative robot. But because we can turn that up. And because of the construction being more industrial, this ultralight, collaborative, light aluminum construction, we can handle moving fairly quicker, and not have to worry about nuisance trips and things of that nature with the sensors thinking that, oh, this might be a person. But you have to do that with something like a safety light scanner. You have to do that safely. You have to prepare for that. So, it's kind of like the industrial safety scanners on the industrial robots that I was telling you about earlier, that it can sense when someone's in there with it, well, it's going to stop. Well in our case, we won't necessarily have to stop, we can slow down, we can turn up the sensitivity on the sensors, and go into a collaborative, safe collaborative speed that most safety coordinators would be, and health safety folks would be happy with. And then but then as soon as someone leaves, we can kick back into the higher speed, turn those sensors down.

Beth Elliott  33:41  

It can be that quick? 

Brandon Ellis  33:42  

Yeah 

Beth Elliott  33:43  

Okay. Okay. That’s nice.

Brandon Ellis  33:44  

And so, there's no reason to have to go slow all the time. So industrial robots don't have to do that. But if someone gets in their way, they stop. They have to. 

Beth Elliott  33:56  

Industrial? 

Brandon Ellis  33:57  

Industrial robots. But a collaborative robot would slow down. It doesn't have to stop. 

Beth Elliott  34:03  

Okay. 

Brandon Ellis  34:04  

Did I say it backwards? 

Beth Elliott  34:05  

I thought industrial robots would just run into you. 

Brandon Ellis  34:09  

Well, I mean, if it's done safely, it will stop. If there's no safety, yeah, it'll keep going and just bonk you in the head or something. But no, I'm saying that if it's guarded with the safety, safety scanner and some set of hard guarding, if you get into its zone, it has to stop. 

Beth Elliott  34:29  

I understand. I gotcha. But the cobot would just slow down.

Brandon Ellis  34:32  

The cobot could, if the risk analysis says it's allowed, could slow down to a speed that's safe enough for whatever tooling that it's carrying and the operation that it's doing. So that is not, the chance, the chance of the amount of risk, I guess is what it comes down to. If there is an interaction between it or its tooling and a human being is minimized. 

Beth Elliott  34:57  

Gotcha. Gotcha. Okay. Do you want to go through the next ones? We did dispensing and gluing. Oh, yeah. So, the dispensing and gluing they're, it's good in the medical and electro electronic and alternative energy, oil and gas and food. Hanwha

Brandon Ellis  35:13  

The HCR-5, five-kilogram robot. Yeah, that's a, that's a good point. So that's the other thing we love about the Hanwha is they, their, their HCR-5, only the five-kilogram model, is full cleanroom rated. And so, in a lot of those applications you just rattle off, that's very important. And actually, in electronics manufacturing and things of that nature, cleanroom is getting more and more required. So, the fact that we can have a robot, collaborative robot that is cleanroom rated is certainly, certainly advantageous. 

Beth Elliott  35:18  

Yeah. 

Brandon Ellis  35:18  

So, then we have, we talked about dispensing, gluing. 

Beth Elliott  35:51  

What about pick and place? 

Brandon Ellis  35:52  

Pick and place, again, that's great for collaboratives. But you have to have certain things come into play. Now we can add vision systems and things of that nature. You have to be able to see where the part is, or it needs to be fixtured. And so, if it can come down and consistently presented, you don't need the vision system. But there again, very easy from a direct teach standpoint, to program that to say, Okay, come down to this point for this particular part, you're going to come here, and then we're going to tell the gripper to close. And then you're going to come up here, and you're gonna move over here, and you're going to come down here, and we're gonna tell the gripper to open. Of course, there's palletizing routines and things of that nature that are canned, and in most collaboratives nowadays to where you can say I'm choosing one point in an array, if you will, some rows and columns and I'm just going to tell you what the offset distances are. And so, you're just going to go from left to right for this many pieces, and then you're going to shift down and offset and go from left to right for that many, same number of pieces, and that's called palletizing routines. And so that's where we're, we're, you're not having to teach every one of those points, placement points. As long as the product is consistent, you can do that. And direct teach makes that extremely easy to do. And then it's just a matter of do it. So, pick and place is that kind of thing. 

Beth Elliott  35:53  

So, you don't have to have advanced vision systems then?

Brandon Ellis  37:16  

Well, the vision systems, all a vision system does is give a robot eyes. And so, there's, there's, of course, there's standard vision systems, which really are 2D, just looking at X, Y, and maybe a rotation angle, if you have to pick it up from a rotational standpoint. But it doesn't really tell you the height, and so that's a 3D based system. And there are 3D systems out there. All of these have cost, and some level, according to the brand, I guess, some level of complexity. They have to be programmed in a certain way and then they have to communicate. So, there's communications and that kind of stuff. The thing that makes cobots so great, is you can put them in applications where they don't have to interact with anything.

Beth Elliott  38:01  

Oh, so you could just let them, you could just direct teach them and then walk off and let it go?

Brandon Ellis  38:08  

Well, they don't have to, if they're interacting with a with a machine, there's clever ways to not have to cut a, strip a single wire and not have to set up fieldbus communications or any kind of communications link between the machine and the robot. It doesn't work all the time. But there's some clever ways to do it. And so, I want to talk about some of those, we're not quite there yet on your list. So, you mentioned on the on the list here pick and place, but also quality inspection and testing. Again, quality tests, quality checks, the cobot could grab it, go in, do some things with it, put it in front of sensors, put it through in micrometers, things of that nature, whatever we're doing for QA inspections or maybe it's a vision inspection. It's possible to pass a part beneath a fixed camera. You can pass the, you can hook the camera on to the robot and move it over the part. But remember, every robot including industrial robots, is always moving on a small level, because of servos and they're always adjusting. And vision systems, especially highly accurate vision systems, high what we call high pixel count vision systems, can pick that up. And it can cause issues with the vision system if the robots trying to hold the camera. But if the camera is fixed onto a rigid deal, and it picks up the part and can move it beneath the camera, that works nearly all the time.

Beth Elliott  39:31  

Okay, that's the ideal setup.

Brandon Ellis  39:32  

Yeah. And so, you really got to look at your application, what you're doing there, but that quality, again, quality inspection, you can see how that direct teach would come into play. And also, according to the part weight, or if you're reading a barcode or whatever you're doing a barcode scanner, those kind of things. Again, typically we pick up the part and move it beneath those things. But even if you're moving the cameras, they're fairly lightweight. And so, you can, you can do this especially if it's a huge part, you know, or a very, very heavy part, you can move those things around. Barcode scanners are nowadays, so, so doggone good. And of course, we combine that with some of our stuff with our Datalogic stuff. So, we can read barcode, read barcodes and do image inspection and things of that nature. But even if you had to do two things, you could have a barcode scanner on the end, and also a camera on the end and do a rotation or something like that. So, you can use each one. But you still have to trigger those things. So, there's, there's interaction, usually that's controlled by the robot a lot of those are smart enough to do that. We have companies that build grippers and different types of end of arm tooling that work directly with our robots to simplify that. But that that's going to be kind of the same with industrial as far as that interaction. That's still not the most clever way to use a cobot. So, let's, let's keep going down your list, because I know it's coming.

Beth Elliott  40:59  

Machine tending 

Brandon Ellis  41:00  

Exactly. And so here is where I think cobots are fairly, a no brainer, because of the direct teach, but also, when I remember when I first there was a time that I first showed a video of collaborative of a collaborative robot being used to our engineers. And it was a machine tending, a very simple machine tending application where basically, the collaborative was reaching in, small parts, small payload, but it was reaching into this machine. Well, first, the machine had a door, but it starts with the door open. So, a sliding door that slid left to right. It might have been a lathe, it might have been a machining center, I don't remember, may have been a press, but it had a door, a safety door that had to be closed. So, the video starts, and that door is already open, and the robot grabs a part, it's empty, and the machine is empty, so it grabs a blank part, and reaches and puts it in place. And then it comes back out. And it's got a little appendage, if you will, end of arm tooling, like a finger, and it reaches over and it grabs the handle on the door, and it pulls the door closed. And then it takes that same appendage, and it goes over, and it presses the start cycle button. The machine starts running. When it completes, it uses the same finger to open the door, goes in and gets the part, drops it out. Does the process again. Well, as soon as that robot used that little finger to push that start button.

Beth Elliott  41:03  

I bet that changed the world.

Brandon Ellis  41:45  

All the controls engineers in the room did exactly what I was hoping they would do. And they erupted and said, why would you do that? Why wouldn't you connect I/O? Why wouldn't you do a fieldbus? Why don't you do all this kind of stuff? And my point was because you got to think differently, or you're allowed to think differently with a collaborative robot because of this direct teach. And because of the fact that you don't have to be a controls engineer, and you don't have to be a programmer. You can, anybody can make a finger. You can put a screw on the end, whatever, you can make a finger, and that'll push a start button. And if there's no danger of the machine starting, you know, on its own and that kind of stuff, then you can do that that way. And of course, the question I got and if you're listening to this, hopefully you're thinking the same thing. Well, wait a second, you got to have some interaction with that machine to know when it's done. When did it finish processing and the parts now available to come in and get? Well, all these machines nowadays have some tell to be able to tell that for the most part, a lot of times it's a stack light. 

Beth Elliott  43:40  

Okay

Brandon Ellis  43:41  

And so, we can install a sensor on the stack light that just looks at the light. And when that light comes on, it tells the robot Okay, do your thing. Now, that's a that's a very easy integration, because we're tying into the robot and that's it. We're not having to get involved with this machine. We're not having to split wires. We're not having to do any, you know, program it, program this one. You're able to do those kinds of things and think outside the box. And that's what, that's what I love about collaboratives is, is how many people have come up with stuff. You know, it's honestly, the same kind of feeling I get, and level being enamored with 3D printing. When I look at the, especially the hobby guys, but even you know, like Matthew Stuckey, who is our intern, who has done a ton and was you know, It Doesn't Have To Be 

Beth Elliott  44:31  

Machined

Brandon Ellis  44:32  

Machined, was the podcast episode where we were talking about 3D additive manufacturing. The stuff that he thinks about and comes up with is just some of it genius, some of it useless but some of it genius, because they're able to think outside of the box now. With our IIoTA and the in the fact that you can grab any data you want to get from pretty much any PLC or device down there, now gives way to a freedom of thinking that just watching people expand their minds. And collaborative robots are kind of the same way over industrial robots, because this direct teach now empowers me to do something. Because I'm not a robot programmer, you know, the person may say, I'm not a robot programmer, but I can, I can do end of arm tooling. I'm a mechanical guy, I can, I can put a shoulder bolt on the end of you know, this robot and make a finger out of it. You know, those kinds of things just make just really make me giddy. I love seeing folks really think outside the box and do clever things like that. We talked about that, even with the FIRST Robotics stuff, with Morgan Everett, when I was talking about going in there and seeing what some of those kids, sophomores, freshmen, sophomore, junior, seniors, and looking at some of the clever things that they come up with, and ways that they have applied tools that were commonly used for this, but they had repurposed them for that. And to be able to have that freedom of thinking is something a collaborative robot gives in terms of industrial manufacturing, because it really comes down to that direct teach capability, is you're not having to do hard programming. And then there are there, there are collaborative platforms that have been around for ages. And they're still an old style of programming that I really don't prefer, I think it's hard. I think it's difficult for folks. The Hanwha interface is a drag and drop, storyline type programming. I love it. It's just so simple to look through. It's a storyline. It's like a storyboard. And when you play it, you can see you're going through the steps. And if you don't want this thing to happen, you just drag it away, and it comes out of the list. And so

Beth Elliott  46:42  

Allison did that video.

Brandon Ellis  46:43  

That's right, she did a video on it. Allison's are one of our sales engineers. And she made her own video for a customer to see. She had never been around that robot, ever. And I gave her the instructions. And she probably is a lot like me in that regard. First thing she did was say I'm not gonna read the instructions.

Beth Elliott  47:02  

Who reads instructions.

Brandon Ellis  47:04  

And in 30 minutes she had, she was, she was ready to make that video. And so that's a testament to how things have progressed in this collaborative market. And so, it just brings about a freedom of thinking outside the box, because you don't have to worry about all the reasons why you can't. And so that that's what I like about collaboratives. Now you've got also assembly, screwing, screwdriver applications, that kind of stuff. And oh, we were also we were talking about

Beth Elliott  47:34  

Oh, machine tending we had plastic injection and blow molding. 

Brandon Ellis  47:38  

Yeah.

Beth Elliott  47:39  

That's under machine tending. 

Brandon Ellis  47:40  

Well, so 

Beth Elliott  47:41  

And that is for like the robot that was standing in front of that door, open it and close it, a person would have been there

Brandon Ellis  47:48  

Right 

Beth Elliott  47:48  

To do that. And 

Brandon Ellis  47:50  

All day long. 

Beth Elliott  47:50  

Oh, my goodness. Could you imagine how boring that would be. How many podcasts could you listen in a day?

Brandon Ellis  47:58  

Yeah, that's the thing. Those are menial tasks. And, and they're also ergonomic tasks. So, they can be damaging. Again, reduction of labor, listen, it doesn't mean get rid of people, put them out in the street. What it means is reclassification. So having a person standing there all day long doing that, when there's plenty other jobs that that person could do that, a collaborative can't do, is what we're talking about. And so really, it comes down to ROI, return on investment. But you said machine tending and then you said injection mold machines and blow molding machines, I kind of put those in the same category. Because whether you're closing a clamp and injection injecting, now you may have to have a bit more interaction with those kind of things. Because an injection mold machine typically, it that's when you're injecting plastic or rubber or something like that. So, there's temperatures involved and those kind of things.

Beth Elliott  48:16  

Oh, they've got to be overseen a little bit more.

Brandon Ellis  48:51  

Well, when they pop the dies open, it's like getting the ice cubes out of the old ice tray. So, you know, sometimes they pop right out and sometimes you really have to crank those things and that kind of stuff. So, what they do is, they install pins, steel pins or harden pins inside the dye that when it opens up exposing the part, these pins basically eject the part. And so, they knock it free from the dye around it. A lot of times there's release agent and stuff like that that comes kind of like spraying, what is it? 

Beth Elliott  49:06  

Pam

Brandon Ellis  49:21  

Pam in your frying pan to make your eggs come out. Those kinds of things. But still, those pins will knock it out. Well. You don't want it knocking it out until the robots ready to get it. Now also a lot of injection molding machines, and that's honestly where Hanwha got its start. Now we don't do the injection mold robotics that they do. But they've been doing injection mold, Cartesian robots for, for years. And then they got into the collaborative market about six years ago. So, they've been in it, it's not they're not brand new. They're just new to us.

Beth Elliott  49:51  

They were one of the first to do the autonomous 

Brandon Ellis  49:54  

Autonomous vehicle. 

Beth Elliott  49:54  

Yes, yes. In Korea. Yeah. Yeah.

Brandon Ellis  49:57  

Yeah. And so that's another thing AGVs, Automatic Autonomous Guided Vehicles, or Automatic Guided Vehicles, AGVs kind of go around the plant. And they're, they're kind of a small box version of R2-D2, so to speak. They just roll around. They can follow paths. They can be pre-programmed. They're looking out. They've got all the LiDAR systems and stuff like that to make sure that they're not going to run into anything or anybody. But all they are, you know, that they're primarily used for, they come up and stop, and a person will load them with stuff, and then off they go, or take stuff off, or those kinds of things. But you can stick a collaborative on the back of it. 

Beth Elliott  49:57  

Yeah. 

Brandon Ellis  49:58  

And the collaborative rides around. 

Beth Elliott  50:36  

Oh, wow. 

Brandon Ellis  50:37  

And so, when they pull up, the collaborative does some things and that kind of thing. Again, usually you're going to want some vision systems in play, or those kind of things. But it can be done and is becoming more and more commonplace. Well, it's, it's still new, but we're hearing about it more often. So, the AGVs and stuff, yeah, they've done they've been in, but again, back to the

Beth Elliott  50:57  

Sorry, I didn't mean to go down that rabbit hole.

Brandon Ellis  51:00  

That's a totally different non collaborative, Cartesian system that they were doing before, specifically for attending plastic injection mold type machines, where you open a die, pop the part out, so this would come down. And its interfaced very tightly with the injection mold machine so that it says, Okay, I'm in position now pop the pins and that kind of thing. So usually, you have to have a bit more interaction, you may have to with an injection mold machine. But if what you're doing if you're just dropping parts at the end, or you have one of those systems that's taking them away once they're once they're done. You may, sometimes injection mold machines, just make plastics. And it's just close the die, squirt in the plastic, open the die, eject the parts, close, and just keep doing that over and over. But there are times where you have things that you need to add. So, we can combine things with injection mold machines, so we can put a piece of metal in, we can put something like that. And then the injection mold machine is, is molding around that piece. You know, it's part of it, partially or

Beth Elliott  51:37  

Like a popsicle.

Brandon Ellis  52:02  

Yeah, yeah, like a popsicle stick, actually. So, you put the popsicle stick in, then you freeze it, and it comes out a popsicle, but you've got to put the stick in first, you can't put it in last. And so that is a good opportunity for a collaborative, that's a menial task. Just picking stuff up and placing it in the same place and getting out of the way. Those are kind of things that can easily be done. So again, collaboratives have a lot of different applications, a lot of different applications. The fact that the direct teach is there, not so much the safety; you got to think about the safety. But the direct teach that's what gets your mind flowing. And then thinking outside of the box to say, I'm going to interact with this process, but I'm going to interact with it just like a human. How does a human know when the machines done? The green light comes on. That's how they know. Well, let's make the robot look for the green light too. And how does the human get the thing going? They close the door and press start. Well, okay, let's make the robot close the door and press start. That's what you want to do. And with direct teach, you can teach those things very quickly and easily and move on. And so that's the most exciting thing I think about that. And then you got ROI. So, ROI, industrial robots maybe 

Beth Elliott  53:21  

Return on investment 

Brandon Ellis  53:22  

Return on investment. So, some collaborative robots cost a bit more than industrial robots. By the time you put the guarding in there, maybe you're about the same. I'm excited to say that as far as ROI. ROI comes down to how much is this going to cost me to implement this robot to take care of this menial task? Or sometimes you, they want to move them around. They want them on casters. So, we're gonna move them in, lock them in for this. They're going to do this today and then tomorrow we're going to go over here and do this and run this other program and that kind of thing.

Beth Elliott  53:53  

That's another, can they do that with industrial robots? 

Brandon Ellis  53:56  

Not as easily.

Beth Elliott  53:57  

Okay 

Brandon Ellis  53:58  

Because you're having to move all the guarding too.

Beth Elliott  53:59  

Yeah, okay. 

Brandon Ellis  54:00  

But if you're only guarding is a light scanner, safety light scanner, then you can have the thing on wheels and slide it around. So, it's much, it plays into that concept a bit better. But then your ROI decides how much money am I going to have to spend? How much am I going to get out of it? So, if I'm taking people and repurposing them to a task that we're having, you know, we're having to look at potentially adding more people to do, we can pull them off these menial tasks and get them involved and repurpose our people in house then that's a direct labor ROI. Because now we've got this robot doing this menial and then also if you're not having to deal with out, you know, out time being out and things of that nature.

Beth Elliott  54:43  

Vacations, sick time, 

Brandon Ellis  54:45  

But, but really 

Beth Elliott  54:46  

COVID

Brandon Ellis  54:47  

COVID those kinds of things, but also ergonomics, you know, you can only. Truck drivers can only drive so much without having to take a nap. Humans must take breaks, you must. Production engineers, manufacturing engineers do a great job with that, especially from an ergonomic standpoint, they'll rotate them. So, you'll do this task for a while, and then you go do a different task so that you're doing a different movements, not wearing the same tendons and ligaments out the whole time. But if you can eliminate those points that are really bad for people, then do it because it's better for your people. Everybody's happier when they're not hurting. And so that's what collaboratives bring about. And the ROI comes down to, you know, what, what, how quickly can I win back my investment, and Hanwha is price so, so, so well, that we have one of the best ROIs in the industry. Again, I'm kind of plugging my own robot, but hey, it's my podcast. I'm paying for the podcast. If you want to be a sponsor, then I'll plug yours, I guess. I'm the sponsor. But seriously, most collaborative robots, all of them support direct teach. And that really is what makes the magic happen, I think as far as what's that song, free your mind. So that's what gets people thinking outside of the box thinking, and it's incredible to see.

Beth Elliott  56:12  

All right. Did you want to go through assembly or the finishing tasks?

Brandon Ellis  56:17  

Well, we talked a little bit about that with the screwing and stuff. Again, assembly machines, unscrewing screws, screw drive systems, you're telling a screwdriver do it, but it's really close to pick and place. Because you're not picking something up, so you don't have a gripper, you have a screwdriver, but you're still moving point to jump into point to point to point to point. But you're, you're telling a gripper to close. You're telling a screwdriver to drive. And then the screwdriver tells you when it's done, you know, the gripper may not. So, but as far as the programming, it's very similar to move to this position, go down here, drive a screw, versus move to this position, go down here, pick up a part. So, pick and place and assembly kind of come into play.

Beth Elliott  56:55  

They should have gone under the same thing.

Brandon Ellis  56:57  

Now there are some industrial and collaborative robots out there that have more than one arm. 

Beth Elliott  57:02  

Oh?

Brandon Ellis  57:04  

We don't represent any of them. But they're, they're dual arm type robots.

Beth Elliott  57:08  

Hanwha has one where you, it can go, you have one controller and two cobots.

Brandon Ellis  57:13  

Well, you could do two separate arms, but I'm talking about they're connected together like C-3PO kind of thing, yeah. Anyway, the nice thing about that is, if you have, you know two hands is better than one. But if you're if you're working together, and that's what I'm talking about, having two collaborative robots that are still programmed separately. But with these other models, and they're more expensive models, I'm sure. But they actually have the ability to have two, two arms that are coordinated. So, one could come in and grab the part and the other one could come in and do something to the part with the other hand. So, deburring and, and those kinds of things. Right now, to deburr a part, we may have the part, pick the part out or something or it's in a fixture that's holding it, and then we would move the deburr tool around. Deburring is taking rough edges off and things of that nature. We may move it around; you know a certain path. And that certainly that's a great collaborative concept, or application. But if you if the fixture if there's a part that you can't get to, because physically because it's sitting in this fixture, if you're able to hold it, and then if that arm is able to set it down to a fixture, grab it from the other side and pick it back up. You can the other arm comes in with the tool. And so those kind of things are pretty interesting. We can certainly do that with two arms. But as far as those being tied together, coordinated, there, there are robots out there that do that both industrial and, and collaborative. Again, we don't represent any.

Beth Elliott  58:41  

That's interesting though.

Brandon Ellis  58:42  

I take that back. No, we. Yeah, we don't currently represent any. If that changes, I'll let you know. 

Beth Elliott  58:49  

Okay. 

Brandon Ellis  58:51  

It makes for an interesting thing. You, it, these are all industrial robots, but there's the bartending robots and stuff like.

Beth Elliott  58:59  

Yeah, the picking the, yeah, we had a couple of unique applications for cobots. But the picking plants I think that was a real cobot. 

Brandon Ellis  59:09  

Yeah

Beth Elliott  59:09  

But the bartender and the 

Brandon Ellis  59:12  

All the ones that I've seen 

Beth Elliott  59:13  

Flipping the hamburgers. 

Brandon Ellis  59:14  

Yeah, Flippy.

Beth Elliott  59:14  

That's not really collaborative.

Brandon Ellis  59:16  

Those are industrial robots. They're not collaborative. They've been set up with safety, again, so that the light scanners and that kind of stuff. Well, the bartending robots are usually technically hard guarded, because the bar's really long. And so when they're making your drinks or they're behind glass or something like that. There's a dual arm one that is a bartender and it's pretty neat to watch but having two arms lets you mix a good drink. One arm is a little slower, but

Beth Elliott  59:49  

Won't be getting your drink as fast.

Brandon Ellis  59:51  

But even in those situations, you know, I've been out in Vegas and saw I don't remember even what brand it was. But it was they were mounted from the ceiling, articulated arm robots, but standard industrial robots but the enclosure and the bar and stuff when they make you the drink, they end up sending it on a conveyor belt or something but it comes out to where you are, either through the glass or you're separated so far away that you can't reach them, again and you know, without climbing up on the bar and going, and then there's sensors, that if you try to do that they would shut down. So, there's safety all over the place. But it's fun to see.

Beth Elliott  1:00:28  

Yeah.

Brandon Ellis  1:00:28  

Some of this stuff. You know that those things are so elaborate and so expensive. I don't know what the ROI on that is. I think I'd rather pay the bartender at least I can talk to him. But nevertheless, it's its wow factor, right? 

Beth Elliott  1:00:42  

It is. Yeah. Well, that's all the applications I had. Oh, yeah. The other one was spinal surgery. I don't

Brandon Ellis  1:00:50  

I'm not doing it.

Beth Elliott  1:00:53  

Or copilot? 

Brandon Ellis  1:00:54  

Yeah. 

Beth Elliott  1:00:56  

Would you want a cobot as a co-pilot? 

Brandon Ellis  1:00:58  

I don't think I need that. I've got a very good autopilot that works. I don't know, I don't even know what that would look like, but that's that out of box thinking, I guess. 

Beth Elliott  1:01:09  

It's fantastic. 

Brandon Ellis  1:01:09  

People are trying different things. I don't know. I don't know if I want that airplane flying over my house though and get a couple, couple more hours of testing on that. You know, one thing we do have, though, and this is a good segue to our pre-engineered work, work cells, robotic work cells. And that's that certainly Hanwha is part of that. So, the stands all integrated. And what those are, you know, we're talking about this empowerment and how direct teach can bring out these thoughts, because the fact that you don't have to be for certain things, you don't have to be this top-notch programmer. And then I talked about the simplicity of our Hanwha interfaces, and that kind of stuff with the drag and drop. Now certainly with our industrial robots, they're still teach pendant based and they have to be, because it's just a different product for different applications. But a collaborative robot being able to do the direct teach, and the simplified programming is what it's all about. So, the engineer work cells, the robotic work cells, the idea is that we take care of a lot of the heavy lifting and meet the customer where they need us to be. And so instead of them just, here's a robot, good luck.

Beth Elliott  1:02:14  

Yeah,

Brandon Ellis  1:02:14  

They may say we're comfortable doing the programming. Even with our industrial product, they have that capability. But what they don't have is they don't have the fabrication to fabricate the tables. And maybe they want to do hard guarding or light curtains or safety scanners or need a place to mount the controller or that kind of thing. If it's the collaboratives, they want the stand to be you know, adjustable, so that it can handle the capacity, maybe on wheels, maybe they're gonna nail it to the floor, whatever, those things are already engineered. So, you don't have to pay for the engineering again on those. And of course, we don't hit all of them, we hope to hit 85% of the things out there. But if the if you're an end user, and you feel like I can take care of my own end of arm tooling, we can we've got a, you know, machine shop or a machine shop to deal with or something, we can design it up. And we can program it. But we don't want to have to deal with all the other stuff, the pedestals, the stands, the tables, that kind of thing. We've got those all built up already. We can tie into the safety circuits and everything like that. If you want us to help with the end of arm tooling, programming, integration, that kind of stuff, we certainly can. We've got the vision systems and all that kind of stuff that we can add on. But the idea is instead of being typical robot integrator where we go in and say, here's your price for everything turnkey, which we can certainly do, we want to leave some spots open for those folks that do have that capability in house. And they say we can take care of this, this and this, if you all can take care of the rest. That's what we're wanting to do. And that's what we accomplished with those. And so, so far, those things have been a hit, and they're growing more and more in popularity. And so, we want to make sure that you all know about that. You can go to our website www.ellitek.com. That's elliTek.com and check those out. But the Hanwha robots, collaborative robots are part of that. So, and then the industrial robots are also part of that.

Beth Elliott  1:04:03  

Yes, yes, they do what they can do. And we'll fill in the blanks.

Brandon Ellis  1:04:06  

Yeah, we want to meet our customers where we're where they are. And, and so it's a good opportunity for them to save some money potentially and get a lot of productivity done.

Beth Elliott  1:04:17  

And it's a quick install.

Brandon Ellis  1:04:19  

Should be. 

Beth Elliott  1:04:19  

Should be?

Brandon Ellis  1:04:21  

I mean, if all you're doing is a robot. Now, a lot of times there's other things around that robot. And if you're doing the end of arm tooling, and that kind of stuff, you know, you certainly have to get that put together. But our engineers work closely with your all’s to make sure you have what you need. And we'll go from there. So, we're but overall, we're excited about this. And the fact that "Industrial Automation - It Doesn't Have To... Be Menial". 

Beth Elliott  1:04:42  

Menial. Yeah. I loved your outlook on the cobots. 

Brandon Ellis  1:04:46  

Yeah

Beth Elliott  1:04:47  

It's it's fantastic.

Brandon Ellis  1:04:48  

It really is.

Beth Elliott  1:04:50  

Because it's opened a whole new door. I mean, a whole new world.

Brandon Ellis  1:04:53  

Yeah, just amazing to see how people are thinking to use these things. And again, you enable them, you empower them, and minds can start working freely, knocks down a couple of obstacles and move. But remember, they're still robots, and they need to be treated. And there needs to be a risk assessment and be careful, especially industrial robots. So, we don't want to take away from that. So, Beth 

Beth Elliott  1:05:19  

Yes, Brandon. 

Brandon Ellis  1:05:19  

Rolling to the end of yet another. How many downloads we got now?

Beth Elliott  1:05:23  

Oh, it's over 1100. Yeah, we're, it's doing good. Thank you, guys, for downloading and listening, ratin' and reviewin'. 

Brandon Ellis  1:05:33  

Yeah. Good job, guys. Good job. Yeah. Last podcast, I was saying we were coming up on eclipsing 1100. So now we've done that. So, Beth Elliott 1100 plus.

Beth Elliott  1:05:45  

No, it's, it's because of the fantastic content that you and the guests have provided and our listeners. Thank you, guys, for listening.

Brandon Ellis  1:05:53  

Yeah, absolutely. And then one last congratulations. Well, I've been referring to her as this for the last couple podcasts and seeing if anybody would notice, Beth is officially promoted to our marketing manager. She is it. She is running the show. And so, congratulations. 

Beth Elliott  1:06:09  

Thank you, Brandon. I do appreciate it. And I will do my best to live up to the manager part.

Brandon Ellis  1:06:14  

I'm sure you're going to do great. What that really means, guys, is I don't have to do as much anymore, because I'm no good at it. And she's fantastic at it. So, congratulations on that. I'm excited about that. So, guys, listen, have a fantastic week.

Beth Elliott  1:06:26  

If you want to reach out to us

Brandon Ellis  1:06:30  

Oh, sorry. Marketing. 

Beth Elliott  1:06:32  

Our phone. I know. Come on, man. 

Brandon Ellis  1:06:35  

Go ahead. 

Beth Elliott  1:06:35  

Our phone number is 865-409-1555. If you want to visit our website, it's elliTek, elliTek.com.

Brandon Ellis  1:06:46  

And then we've got LinkedIn, Twitter and Facebook. Basically, some form of elliTek. On every one of those. I think LinkedIn is elliTek dash inc. 

Beth Elliott  1:06:56  

Hyphen. 

Brandon Ellis  1:06:57  

Sorry. Hyphen inc. And then Facebook. Is it Facebook, that's underscore?

Beth Elliott  1:07:04  

Facebook and Instagram are just elliTek. 

Brandon Ellis  1:07:06  

Just elliTek. So, it's Twitter, yeah that's the elliTek underscore Inc. So, check us out. Like she says, rate and review, subscribe. We appreciate everybody that has, and we'll continue to do these things. So hopefully you're getting a lot out of it. So once again, now that the marketing is done. So, marketing. Have a great week, everybody and we'll I guess two weeks we'll be out with another one.

Beth Elliott  1:07:33  

Every other Tuesday. 

Brandon Ellis  1:07:34  

That's right. Take care, Beth.

Beth Elliott  1:07:35  

Thank you, Brandon. I appreciate your time.

Brandon Ellis  1:07:37  

See you guys.

Transcribed by https://otter.ai