If you're considering the purchase of a collaborative robot, vision system, or industrial IoT system, this episode is for YOU!
Before making an investment in the automation of a process, there are some commonly overlooked aspects that can be forgotten, overlooked, or even disregarded.
With more than 25 years experience in the industrial automation market segment, Brandon shares his knowledge and experiences so others can hopefully avoid those pitfalls.
For instance, why choose a collaborative robot if you have to guard it? What's the point? What about fast cycle times? Collaborative robots can't go as fast as a person, right? You may be surprised to hear the answers.
As for vision applications, they can be fraught with problems if some details are left out. You won't be surprised to hear that lighting is important for vision systems, but seasonal changes and natural lighting can play an important role as well. Brandon shares several other details that need to be considered, including cybersecurity.
Brandon has seen his fair share of failed or incomplete industrial IoT systems. That's why he invented the Data Commander™ MES Appliance. During this episode, he shares some of the biggest problems that he has encountered.
One of the travesties that Brandon has seen in his career is holding onto a system that doesn't work. Sometimes portions of a system can be salvaged, sometimes not. The best way to avoid the common pitfalls is to ask the vendor to show you how it works.
Seeing is believing. Schedule a demo to see the Hanwha collaborative robot, Datalogic vision system, or IIoTA™ MES appliance, email FreeDemo@elliTek.com.
No matter where you are in your automation journey, elliTek will meet you there!
Here is a link to elliTek's FAQ page, https://www.ellitek.com/faq. This page will soon be expanded to include FAQ on vision systems and IoT systems.
Reach out to us with any questions or future topics!
If you don't want to click on those links, pick up the phone and call us at (865) 409-1555 ext. 804.
If you're considering the purchase of a collaborative robot, vision system, or industrial IoT system, this episode is for YOU!
Before making an investment in the automation of a process, there are some commonly overlooked aspects that can be forgotten, overlooked, or even disregarded.
With more than 25 years experience in the industrial automation market segment, Brandon shares his knowledge and experiences so others can hopefully avoid those pitfalls.
For instance, why choose a collaborative robot if you have to guard it? What's the point? What about fast cycle times? Collaborative robots can't go as fast as a person, right? You may be surprised to hear the answers.
As for vision applications, they can be fraught with problems if some details are left out. You won't be surprised to hear that lighting is important for vision systems, but seasonal changes and natural lighting can play an important role as well. Brandon shares several other details that need to be considered, including cybersecurity.
Brandon has seen his fair share of failed or incomplete industrial IoT systems. That's why he invented the Data Commander™ MES Appliance. During this episode, he shares some of the biggest problems that he has encountered.
One of the travesties that Brandon has seen in his career is holding onto a system that doesn't work. Sometimes portions of a system can be salvaged, sometimes not. The best way to avoid the common pitfalls is to ask the vendor to show you how it works.
Seeing is believing. Schedule a demo to see the Hanwha collaborative robot, Datalogic vision system, or IIoTA™ MES appliance, email FreeDemo@elliTek.com.
No matter where you are in your automation journey, elliTek will meet you there!
Here is a link to elliTek's FAQ page, https://www.ellitek.com/faq. This page will soon be expanded to include FAQ on vision systems and IoT systems.
Reach out to us with any questions or future topics!
If you don't want to click on those links, pick up the phone and call us at (865) 409-1555 ext. 804.
Industrial Automation - It Doesn’t Have to be Vague
Brandon Ellis 00:00
Today we'll be talking about some of the factors to consider before starting an automation project, so plenty to hear, plenty to discuss, join us.
Hello everybody, and welcome to Industrial Automation - It Doesn't Have to... In case you're new to our program, I'm Brandon Ellis and I'm your host and also the owner of elliTek. Before we start today's episode, I just want to ask that you consider hitting the follow button and the subscribe button, depending on the platform you’re listening upon. Also, if you’re listening on Apple Podcasts and you enjoy what you hear, please go to the show page and scroll to the bottom and leave us a 5-star rating and review. Now that we've got the marketing out of the way, I want to say thanks for tuning in. So, let's get started with today's episode.
Hey guys, Industrial Automation - It Doesn’t Have to… Season 3.
Beth Elliott 00:56
Season 3 already.
Brandon Ellis 00:57
Episode 3.
Beth Elliott 00:59
It is.
Brandon Ellis 01:00
So today we're talking about a few things, but first good morning or good afternoon or good evening, Beth.
Beth Elliott 01:06
Hello Brandon, hello everybody. We’re glad you’re here.
Brandon Ellis 01:11
It's a good morning for us. We had a visit that I just really enjoyed, so I want to start out by doing a quick thank you and shout out to Wilson Meyer with the Knoxville Chamber, who have coordinated a visit with Knox County Mayor Glenn Jacobs and his staff, Jane Jolley was there as well, and a couple of others... They came by and visited elliTek, we got a chance to talk about some things, talked to them about some robots and some of the stuff that we do, but primarily some of the training that we do to try to help empower our community, and both large and medium and small manufacturers in this area, specifically in Knox County, Tennessee. I’ve had the opportunity to speak with Mayor Glenn Jacobs a couple times, and I'm just really, always, impressed with his insights, his perspectives, he’s had a rough, rough... Every Mayor in the United States of America has had a rough last year, year-and-a-half, since we’ve gone into this pandemic and, for us, he's handled it, I think, as best as could possibly be expected.
Beth Elliott 02:30
He’s doing a phenomenal job.
Brandon Ellis 02:31
Yeah. We’re grateful to him for all he does for our community. Also, it was just great to have him here. He’s a lot of fun.
Beth Elliott 02:37
He’s very tall. You need to head over to our social pages and see the pictures, because he’s a head and shoulder above everyone.
Brandon Ellis 02:49
It doesn’t take a lot to be a head and shoulders over me. I’m of average size. But I made sure not to stand next to him during the photo. But yeah, we had a good time, we had a lot of good insight and good constructive conversation, so thank you again to Wilson for putting that together, and to the Mayor and for his staff for coming out here and taking some time.
Beth Elliott 03:16
Absolutely.
Brandon Ellis 03:17
So that said, what's our title for today?
Beth Elliott 03:21
Oh, today’s title is “Industrial Automation - It Doesn’t Have To… Be Vague”.
Brandon Ellis 03:28
Vague. Vaguity. The thing that problems stem from.
Beth Elliot 03:33
That’s right, that’s right. So, I want to start with some questions, fire ‘em at ya there, Brandon. Before folks invest in automation of a process, what are some commonly overlooked aspects that need to be considered?
Brandon Ellis 03:49
Well, automation of a process can be a couple of things, you know, custom machine builds, custom equipment, stuff like that. But in this case, the thing that comes to mind for me is end users. And a lot of our listeners, I think, are manufacturing end users of different sizes, that are either the large folks that are listening to kind of hear what’s going on, down to the small to medium-sized manufacturers that are still maybe very manual with their processes and probably are being every bit as affected by the labor shortage as even the largest folks. But the larger folks have deeper pockets, and so they got money to do a lot of stuff. So, for the small to medium-sized manufacturers that really could utilize automation within the plant, sometimes it's not always easy to get to. The thing that most people... As far as automation, the first thing that a lot of folks think about is robots, and more specifically, in the current news, I guess, as far as popularity, is collaborative robots. There's been a push to use collaborative robots for quite some time. We talked about that quite a few times in previous podcasts. You even started a drinking game, because I would commonly say I’ve not seen a collaborative robot used collaboratively, and that means no guarding whatsoever. Not even light scanners or anything. And the reason I make that point is because that's how they're marketed, that's how they're sold. That's one way. And the other half of the coin is you don't need... You can do this in-house; you don't need any outside help from integrators or machine builders or anything like that. Just let me sell you one, here I'll do a quick demo and show you: See I can do direct teach and teach the points and then it's all you. And what a lot of folks have learned is there's more to it than that, because you do have to do a safety analysis, you do have to make sure there’s e-stops in place, the system can be rendered safe, you do have to make sure the tooling is engineered in such a way that it makes sense. I've heard a lot of complaints from folks that... I had one customer tell me “We don't allow any collaboratives in the plant”.
Beth Elliott 06:18
Oh, really?
Brandon Ellis 06:19
And I said “Why? I'm not going to push you; I'm not trying to sell you on collaboratives but why?”. And the answer was: “They’re way too slow, much slower than a person, and they're not as accurate. But primarily they're slow”. So why are they slow? Let's talk about some of the reasons why you can't use a collaborative robot. And these are things that are commonly overlooked, collaborative robots are typically used where we have a person, typically a person that’s performing a repetitive-type task. It's not extremely complex, it's not very hard to do, maybe it's just moving parts, maybe it's picking a part from one position and loading it into a machine, and then picking a part out of that machine and scanning it, or holding it in front of a vision sensor, or another sensor and then if it's good put it one box, if it's bad put it in another box. Those are great collaborative-style projects, or so it would seem. But what people fail to consider really comes down to the four reasons to automate.
Beth Elliott 07:36
Yeah. Brandon’s Brandology?
Brandon Ellis 07:37
Yeah, my Brandology. So, yeah, the four reasons to automate. Quality consistency, decrease in cycle time or increase in production, a re-classification of labor and flexibility and quick setup. Those four reasons… You don’t have to do all four, but one needs to be your goal, but you have to consider all four. Because it can be a trade-off. If my focus is quality and consistency or my focus is reclassification of labor, that doesn't mean I'm going to also have necessarily increased production and decreased cycle time, because there's trade-offs. So why are there trade-offs? And that’s the biggest one. Cycle time, it’s slow. That’s the biggest thing I’ve heard. Collaborative robots are slow. They’re way slower than a person. Well, that's because you're having to slow them down so much, probably, I'm assuming, slowing them down so much because of the shape of the tooling, because of the cycle... You have to slow them down to be safe, because if the tooling is shaped like (I’m holding a ballpoint pen) ... If that’s my tooling, be it a screwdriver or some type of a probe or even fingers on a gripper, if I move that quickly, the PSI calculation, pounds per square inch, is what you have to do on your tooling. When it impacts something, is it putting all the force on a single point or a small area, or is it like a large light object, like a cardboard box or something that's empty, so now all of a sudden the force is distributed across a larger area, so if it comes up against a person or an object that force is dispersed, but if it's all coming to a point, the pounds per square inch... Because the poundage is the same, but the square inch part is very small, so that means it will impel you. And so, you're forced to move slow. That's the number one thing, and that of course is interpreted as it doesn't meet our cycle time requirements. The size of the parts does come into play, I mean if a part weighs too much, it just weighs too much. You can’t take away from the payload capability. And that’s true with industrial robots as well as collaboratives. They lift what they can lift. Now also, if you are able to move within your cycle time but the part weighs a lot, the acceleration comes into play, because collaborative robots have sensors, force sensors at each joint. That's what makes them collaborative.
Beth Elliott 10:31
It’s force, f-o-r-c-e?
Brandon Ellis 10:34
Yes, force. So what we’re doing is monitoring how much force at every angle. So, it may not be just the front coming in, it may be coming across from the side, or hitting here. They're designed and marketed to work right between people without guarding. So, they have these sensors. But the sensors are great, they're very sensitive, but they're not sensitive enough to ensure no damage. Because the fact of the matter is: even if you and I are working side-by-side, and I hit you with this accidentally, you're going to get hurt. The difference is I’m a human, and so when I poke you with a pen and I hear you squeal, hopefully, hopefully, my reaction is to stop doing that. Robots might not react that quickly. The other thing is robots are just moving and even if you've got vision and stuff like that in places, it’s not like a human where I can say “Sorry I didn't see you there”. Which means that the other part of the times I could see you. Robots, they never see you, even with vision. New systems are coming that make that a little bit more that they see. But for today’s podcast we are going to say that most robots don’t see. And also, there’s more cost in that.
Getting back to automating a process and using the collaborative… Why can’t you use the collaborative? It has to move too slow in order to maintain safety or to be able to move the part that I’m moving. In order for it to maintain safe, it can’t move the part because I have to drop the acceleration and the deacceleration so low because it can’t tell the difference between accelerating this part… And that’s assuming the parts can be picked up by the robot… So, to that, I say, just guard it. And they’re all like “Well, if I’m going to guard it, what’s the point?” I might as well use an industrial robot. Well, now, hang on a second. That’s what I want to go through for this question. What are the benefits that you still realize besides not guarding it? Because I have never seen a collaborative robot that’s not guarded. So that money is being spent, it’s either a safety light scanner, maybe some kind of light curtains, or some less substantial guarding. So, put less substantial guarding up, hard guarding in addition to the light scanners or something, it's not going to kill your project, and then you can go faster.
Beth Elliott 13:25
Oh, OK.
Brandon Ellis 13:26
OK. Some collaborative robots, you can go faster. Some of the most popular brands of collaborative robots, at least popular in the United States, cannot.
Beth Elliott 13:34
OK, why?
Brandon Ellis 13:35
Those sensors, those force sensors, cannot be largely or completely disabled.
Beth Elliott 13:42
Oh, the force sensors just going to be what it is.
Brandon Ellis 13:45
Yeah, so when you start moving it faster to get your cycle time, it may be the acceleration of just the mass of the robot itself and not so much a part that's causing it to think that it might be colliding with something. Now, there's one robot line that I know from immediate experience, that we can grossly reduce and override, we do this manually, but we can override the collaborative nature of it.
Beth Elliott 14:11
Oh, who’s that?
Brandon Ellis 14:12
That’s Hanwha Robotics.
Beth Elliott 14:14
Oh, OK.
Brandon Ellis 14:15
We've done that, and we can get some really good cycle times, but you’re going to have to put some guarding around.
Beth Elliott 14:21
Yeah, you have to.
Brandon Ellis 14:22
So, if you guard it, why not use industrial, Brandon? That’s the question. You know, industrial robots and collaborative robots generally have, you can actually... We’ve talked about that in a podcast, you can actually get an industrial robot for less expense than a collaborative. Because you’re paying for those sensors. However, with the Hanwha, and I'm not trying to sell you guys on this, it's just a fact, with the Hanwha Robotics, which is why we picked them up as a distributor and a partner and an integrator, is the return on investment is so great, and that's because the price is so wonderful. So, it's hard to get all the functionality from a collaborative robot, and the flexibility; meaning that we can go in and largely disable the force guided sensors and make the thing non-collaborative. It's going to run and it's not going to stop, and if it does stop, it's going to treat that stop like an industrial robot would treat it, which means a collision. Not a safety stop. A collision. So, collision is what industrial robots do... When we sense a collision, we've had a crash, we call that a crash. Which means that tooling’s come up against something that's not supposed to, or something wasn't supposed to be there, or something like that. But it's tooling against tooling, or guard against guard, or tooling against machine, something like that, not human. Because we have guards. To be able to take a collaborative and convert it into that, to where it will operate like an industrial robot, means that we can start getting those cycle times. Because of our safety, our safety risk analysis or safety audit changes because as soon as we add guarding, all kinds of things change. We can start doing a lot more. So, add some guarding. It's not that expensive to add guarding. And again, you don't have to totally disable those, usually we’ll leave them at the top levels, and we’re able to do a bit better collision detection. Because now you're talking about saving the tooling, saving the robot, saving the tooling. Guarding can be replaced, but you don't want to break your tooling. And to be able to now adjust it so that from a collaborative standpoint we're not looking for human safety, we’re looking for tool safety. Increased tool safety. That's a benefit you get from collaboratives that you can't really change with industrials. What we’re doing with industrials is that we put in their payload. So how much does the tooling weight with the part, how much does the tooling weigh without the part. And then we do those calculations, and it does its own sensing usually. You can go in and modify those but that’s more of an advanced thing to do. But for us it's sliders.
Beth Elliott 17:19
OK, oh. From whom?
Brandon Ellis 17:21
Well, I mean, it’s on the…
Beth Elliott 17:23
Sliders
Brandon Ellis 17:24
It's just how you adjust it, with sliders.
Beth Elliott 17:26
Oh, ok. I was thinking Smartshift Robotics
Brandon Ellis 17:31
Not mechanical, on the pendant. So, with my experience with other robots is you go in and teach payloads and stuff, you've got to go into some very select menus and things of that nature. Which brings me to another point. I’ll get to that point in a second. Right now, you can take a collaborative robot and guard it, get your cycle times, and the number one benefit is you can now use the collaborative nature, if it's a model like the Hanwha that you’re able to disable this. And again, from my experience, I don't know of anybody else that can really do that. The other thing they have is collision mitigation. We use collision mitigation or anti-trap, what this is… If there is... Let's go back to the non-guarded collaborative deal, if the robot does come up against a person, most robots as soon as they sense the collision with the person will put the brakes on lock up and that's where they are, and the arm is held in that position in a rigid stance. Collision mitigation is something that you can enable that Hanwha offers as a built-in feature, which we love. We keep it enabled. It's meant for... if it comes up and hits a person for one second it goes into that direct teach floating posture, which means the robot can relax, it’s allowed to relax off the target. But a person can intuitively push it away and just easily push it away, and then it locks in place there and goes into full-on locked safe mode. It's meant to not trap you up against. That's probably one of the number one safety issues or incidents that I've heard of is with maintenance folks, and even integrators, that just get a little too comfortable, but they're inside with the robot... Usually there's two people inside the robot cell, and they're doing a maintenance-type deal, but one of them has the dead man’s switch and the other is just hands-free, and the robot zips around and does something there and pins them up against the side, and the other person let's go of the dead man’s switch but, you know, it wasn’t them, so they might not have reacted as quickly or something. And now they're pinned up against the wall. I’ve talked to a couple of people, unfortunately, that have been through that, and have been hurt by robots. I mean, they’re really dangerous and they need to be respected, even collaboratives need to be respected. But anyway... The anti-collision that serves to let people push it away, if you're in a guarded situation you can still use that to save your tooling. And then also for recovery. So, recovery of a crash... Crashes happen. It's automation. Machines are going to need maintenance, machines are going to crash, it's just going to happen. What you're trying to do is make it to where you can just recover from the crash, the tooling is not broken, or damaged so you can start again. Because if you can't start again, that's called a downtime event.
Beth Elliott 20:29
Yeah, you don’t want that.
Brandon Ellis 20:30
And then, the recovery is also a downtime event. It's a collaborative robot. With industrial robots, typically from my experience and many others, is when they come up and they have a collision and crash, they lock the brakes right there, and so when you're trying to take the teach pendant and jog it back to move it off of the collision, every time you power it up, it comes on for just a second, it senses that opposite force, realizes it's still in the middle of a collision and faults right back out. And it may move a millimeter.
Beth Elliott 21:04
Oh, my goodness.
Brandon Ellis 21:05
And you just have to keep going, click, click, click, and let it move out a millimeter until it finally relaxes enough. Well, the collision mitigation would overcome that. And so, you wouldn't have all that back and forth, back and forth until you can finally get it freed to where you can keep it enabled and jog it off out of the collision zone. That's one thing that you get with a collaborative robot. The other thing is, just in general, not wrecks and crashes, but the other thing that happens all the time with industrial robots, and probably collaborative robots, I think, is reteaching points. So, anybody can learn to use a teach pendant on an industrial robot. It's not necessarily the most intuitive, it’s according to the brand you’ve got. But it can be done. And the problem with most maintenance folks, and if you're a maintenance manager, plant manager, HR manager, you probably are dealing with this... Is you have to kind of keep your chops up. Especially because most manufacturers got different brands, but with a teach pendant, you have to know which menus to go to, what buttons to push, more importantly what buttons not to push, to be able to move that. And from my own experience, working with multiple robots, just like working with multiple PLC's, I have to step back for a second
and think “Oh, wait a minute, this is this brand, it's not that brand, in that brand I did that in that way, that was what the menu was, in this one this is a different menu” that kind of stuff. And if you forget that stuff, because you hadn’t had to work on that robot. If it's a good product you never have to work on it, which means your maintenance guys...
Beth Elliott 22:50
They’re going to forget.
Brandon Ellis 22:51
They’re going to forget any training that they’ve got. So that takes longer to polish points, do touch ups on points and things of that nature, it also takes longer on recoveries and those kinds of things, troubleshooting. With a collaborative robot, it's pretty easy to remember how to grab the end of the robot and move it where you want and click teach. I mean that’s pretty intuitive. What does that mean? That means less time from a maintenance standpoint, but it also means less need for recurring training, honestly a bit lower skill set requirement. Because if you’re not having to... you teach a skill set, but if you don't use it...
Beth Elliott 23:33
You're going to forget.
Brandon Ellis 23:32
You forget it. But if it's an easy skill set, if it’s simplified, it's a lot easier to remember and grab on again. So, all these are reasons… I don’t buy into… why use a collaborative if I've got to guard it? Because of all these different things, because of direct teach, because honestly that's the reason you wanted to use it anyway. The direct teach, where I can grab the end of the robot, move it where I want it to go or teach a path or whatever we're going to do, that's the cool sauce that everybody likes about a collaborative. And they're easy to use. So, goodness, don't let that stop you. All those benefits go by the wayside...
Beth Elliott 24:15
Just because of guarding.
Brandon Ellis 24:17
Because you need to increase cycle time and you need to stick a little guard around it. Just guard it.
Beth Elliott 24:21
So, what factors are typically forgotten with vision? Because you’ve mentioned vision with the robots, but vision in general.
Brandon Ellis 24:31
Vision is a bit of magic, it's an art for sure. And the reason is that's one skill set that a lot of people feel like a human element should apply more. I didn’t talk much about it, but in robots, we talked about… Go back and look at our past podcast, we talked about the wiggle jiggle. That's another thing on robot process where if you're just picking it up and putting it here in that kind of thing, but if the operator picks it up and does this and drops it down or, more importantly, they're loading apart into a machine and removing a part and they're able to put two hands in and drop one while they pull one, you're not going to match that cycle time, unless you have two robots. It's those little human elements, being able to pick it up, glance at something like this, yeah, looks good and then drop in the bucket. Well, a robot’s going to have to pick it up... Or what if their tooling has... I'm doing this on video: I’m going to take this pen and without touching it with another hand I’m going to move it.
Beth Elliott 25:45
That would be hard for a robot to do.
Brandon Ellis 25:47
I'm going to rotate it around and stuff we do, because we have hands and fingers.
Beth Elliott 25:51
Yeah, but how many fingers does the gripper usually have?
Brandon Ellis 25:54
A human can twirl it like a baton and a robot can't. You have to, as a production engineer, as a manufacturing engineer, you have to watch your process and really think “How would I do this with a robot?”. Well, vision, we tend to look at things with our eyes and say “I can see it. Why wouldn’t a vision system be able to see it?”. And the human eye is much, much more advanced and capable than any industrial vision system. Any vision system. Even your cell phone. The human eye can focus on things in an instant. They might not be able to zoom in, especially for those of us who have to put on the reading glasses and things of that nature, but you know, in its prime it's pretty doggone awesome. Vision systems, you can't just assume that if you can see it, it can see it. There’s a few things to consider there. Lightning is one of the biggest things, ambient lighting. Even if you use the light that's on the system on the camera, or using external lighting, and you get it all working perfectly, and then all of a sudden, a light bulb goes out, or they replace high intensity discharge with fluorescence, and although we can't tell it, fluorescence are actually at 60Hz, 60 times a second flashing on and off, on and off. And some, according to the quality of the bulbs, the fixtures, some are worse than others, well the vision system can pick that up, so all the sudden you end up with bright and dark according to when we snap the picture, as far as the aperture. So, you need to use, usually, integrated lighting or lightning associated with the vision system. But then you’ve got to worry about angles of light. But even if you’re using external lighting it can be influenced by the environment, so just because you have it set up and working in one place, in one environment, you move it to another environment, move to another part of the plant, move it to the plant... I've seen systems where we put it in, had it working perfectly, it worked perfectly for years, and then all of a sudden, they call us and say it’s not working anymore, and what we learn is that they installed a skylight, and so now we have natural light. Or like three weeks out of the year there's a window or a hole in the side of the warehouse or something where the ray of sunshine... We had that happen. Where the ray of sunshine will come in and just go slowly across the machine.
Beth Elliott 28:31
It's just one time of year that it does it.
Brandon Ellis 28:34
Yeah, and it happens, and nobody can figure out why, and by the time you get there it’s gone. It freaks out at a certain time. And these are things that change. You have to be able to control the lighting. An easy way to do that is put a shroud around it, some kind of dark box around it or something like that. There's dome lights, there’s different types of lightning that come into play. A lot of times that’s not considered. The other thing I've seen is people trying to take a vision system to tell, distinguish, between colors. If it's a very different color, even grayscales, if it's black or if it's white, it's much easier than all the grayscales in between.
Beth Elliott 29:22
All the shades of gray that are in between.
Brandon Ellis 29:25
Yeah, is it white or is it off-white. If you're doing that with a black-and-white sensor, which means we’re looking at contrast. If you’re doing colors, though it's ROYGBIV, and more, because vision systems can actually see in the ultraviolet spectrum, the infrared spectrum, and things of that nature. So, what that means is they’re very exact probably comparatively to humans. Because I guarantee and people listening have done this where you say, “I see green, it looks green to me” and you say “well, no. It’s gray”. Or I see brown, and you see gray or green or something like that. Even for humans it's hard to distinguish between blue. For vision systems it's not. It's all digital, it's all values. If it sees blue and there's a variation in the next blue, it says that’s not blue anymore. And there are variations that happen in production. Especially with colors. Colors are hard to keep up with. So, if you're trying to say, “I want to make sure this color is blue”, then maybe you need to change your perspective and say, “I want to make sure that it's not red or yellow” or something like that instead of “I want to make sure that it's blue, and it's got to be this color of blue”. Because sometimes that gets very difficult to do. Because of variations, not because of the vision system, because of variations. You can open that up a little bit but if you open it up too much, then suddenly you kind of risk…
Beth Elliott 31:04
Have a green in there.
Brandon Ellis 31:05
The blue kinda looked like a green. So, blue and green. So, ROYGBIV. You remember that from eighth grade science?
Beth Elliott 31:18
No!
Brandon Ellis 31:19
Those are the primary colors. Red, orange, yellow, green, blue, indigo and violet. And that’s the colors of the rainbow that we see. That the human eye can see, in that order. The R and the V are the farthest apart. Violet, which is purple, and red are the farthest apart. But ROYG, G is green, B is blue, and are very similar in the spectrum. They have that kind of wash over that we see, if you do a lot of graphics design and stuff, you see kind of the rainbow effect of all the colors, as the color spectrum goes, you go from green to blue or blue to green, one direction or the other. Those variations are very difficult to tell. You’ve got to take that into consideration.
Curvature. Curvature. And what we mean is the surface is curved. I always imagine like a container, a pill bottle, or a drink bottle, a Cola bottle, or any kind of bottle, Clorox wipe bottle, something like that. Especially if you’re trying to do optical character recognition, we call that OCR, as it curves on the surface, an O doesn't start looking so much like an O anymore. A C can start looking kind of weird. An R, anything can start looking weird. Unless it’s like an I, but an I can actually disappear and move in with the other parts. It’s according to how intense the curvature is. Those kinds of things come into play. So just because you can see it, doesn’t mean it will be able to see it, especially if you’re trying to read it. You have to take into consideration your tools.
Another thing is field of view resolution. So, resolution, we measure that in pixels. If you own a cell phone and if you paid attention at all to the camera. Mine’s got 12 billion pixels or whatever they are now. Four cameras, five cameras.
Beth Elliot 33:32
Mine has five.
Brandon Ellis 33:33
Yeah. Those cameras are really powerful, and they make large files, data files. It's because they have large resolutions which we measure in pixels. They need to, because they're there to record life. Industrial vision systems can be high-resolution, but usually they're pretty expensive, cost goes up based upon resolution. But why would you need high-resolution? Well, if you have low resolution… What that looks like is you're taking a large area of colors, or if it's black and white contrast, and you’re kind of taking an average and turning that into a square. If you want to know what that looks like in low-resolution, for those who are lucky enough to have ever played with an Atari, or ColecoVision or even the first Nintendos, you know Mario was a little blocky in his complexion. And so is the gorilla in Donkey Kong and stuff like that. That's low resolution. Vision systems work the same way. If you need to see something really close and see contours really smooth and stuff like that, you may need low resolution or high-resolution even at being really close to the part. But usually, we go high resolution when we need to see a greater field of view, so we need to see more of it. Instead of looking in and seeing a very small area, we need to see a larger area. So, you have to take that resolution and increase that. Well, just because you increase the resolution doesn't mean you're done, you still have lenses. Like on a regular camera, good old cameras, not camera phone cameras, they have mechanical lenses. Zoom lenses and things of that nature.
Beth Elliott 35:21
They get fancy too.
Brandon Ellis 35:23
Yeah. They get expensive. That's the things that I think are typically forgotten about with vision. Because here's a general cost for vision system, okay but we didn't consider that we're trying to see this across a 2-foot range of interest and we need to add a zoom lens, we need to double your resolutions, and all that. Well, now all of a sudden, your vision systems twice as much. We need external lighting, we can't use the internal lighting because it’s too large of an area, or we're washing out what we’re looking at from the direction with the built-in lighting, so we need to do indirect lighting with external vision, we need to shroud the thing, all those are just adding to the cost. All that's fine if you know that when you're budgeting. If you start into a project kind of haphazardly, that's what I've seen, the money starts going way beyond budget and people don't like that, and then the ROI calculations go out the window and that kind of thing. So, that’s one of the things.
The other thing is cyber security, believe it or not with a vision system.
Beth Elliott 36:28
I bet you can hack into that.
Brandon Ellis 36:30
Well, it’s about hacking but... So, your vision system is just a camera with a little bit of memory on it, it’s according to how you’re using it. You can use a vision system kind of like a discreet sensor. It snaps a picture, and it gives us an output or result of good or bad, pass or fail. And then I don't care about the image anymore, I'm going to take another one, wipe that one out, let it go, we don't need that kind of thing. But a lot of folks want to keep the images. Well, most cameras on the market, the way they've always dealt with that is a picture is a file. If you’ve ever taken a picture with your phone, it creates a file, you email that file, you do things with files. There's applications that do things with files. In this case a photo is a file. When you're transferring that, you have to use a protocol, a language that computers understand, to transfer that. And we refer to that as file transfer protocol or FTP. A lot of camera manufacturers support FTP, and so that you can take that image and if you have an FTP server set up, that is on a PC or a PC-based server, it can FTP that over. FTP typically uses a specific port on the network, port-21. There's a secure SFTP, which is a secure file transfer protocol, which is a bit more secure, but from an IT standpoint, it doesn't cut it. So, FTP absolutely doesn't cut it, because if it can transfer through port 21 a file, anything that gets on that site can use that same port. There's things you can do to try to get away from that, but a lot of IT folks, four, five or six years ago, IT department started locking out, locking down port-21 to make that port unusable. FTP needs port 21 to work, so now you have to kind of consider that as well. If you're running into that and you want some really cool concepts of what we may be able to do to help, our IIoTA can give some capabilities. That’s all I say about that. When you're dealing with that on a camera system, you have to make sure that, if you want to store those images, that you have a way to do it. And right now, it requires FTP and if it doesn't meet with your cyber security requirements in your plant, you have to rethink it. Rethink it before you start, not when you're in the middle of the project.
Beth Elliott 39:14
Well, do you want to move on to the next… Pre-pandemic estimates by IDC International Data Corporation say that manufacturing is the biggest spender on IoT technologies with almost 200 billion dollars spent for discrete and process manufacturing. That is a lot of money.
Brandon Ellis 39:41
A lot of money, I don't have a ch-ching in here.
Beth Elliott 39:44
So, with 200 billion dollars spent, and that was before the pandemic, what are some of the biggest problems that you found with manufacturing implements on IoT systems? I mean, that’s a lot of money to be spent.
Brandon Ellis 40:22
You know, IoT has gone through a lot. elliTek is a distributor, a regional distributor for products. We offer integration services for the products we sell as well, and that's more regional. I’ve just mentioned our IIoTA. And when I say our IIoTA, it’s our IIoTA. I’ve invented it, and we've developed it in 2014, it was called the Data Commander, and we changed it to the IIoTA because the IIoTA has more capabilities. It stands for Industrial Internet of Things Appliance. It’s an acronym. We like acronyms.
Beth Elliott 41:03
Oh, we do.
Brandon Ellis 41:03
That said, it's a large portion, it’s a global portion of our business. We sell IIoTAs to various industries across the entire planet, but we have seen, and all of IoT has seen, a really a decrease in spending through the pandemic.
Beth Elliott 41:26
Why do you think that is?
Brandon Ellis 41:28
Well, I think that we were seeing a downward trend in IoT anyway coming into the pandemic, because honestly… pre-pandemic numbers, right? Because honestly, you know how I'm hard on marketing folks, there was a lot of high dollar, high-budgeted marketing rhetoric out there that wasn't very good, very accurate. It was telling people what they wanted to hear, and people were allowed to hear what they wanted to hear, so there was a whole push for the spending in that. So, I believe that folks finally got to the point where they were kind of done with all the marketing, and ready to just shelve that for a while. Especially when they were implementing it and it wasn’t giving them what they wanted. It was OK pre-pandemic to just shelve that, the reason… Do you remember? The reason to have an IoT system is...
Beth Elliott 42:31
To make educated business decisions.
Brandon Ellis 42:35
That’s right. Yay Beth. Everybody hear that. Let that sink in. The purpose of an Industrial IoT system, the only reason to have it, is to allow the organization to make educated business decisions to figure out how to better grow their business. To empower them. And if it's not going to do that, or the most horrible concept is if it's going to give you data that's erroneous, that's not accurate, that's misleading, you need to turn it off. You would be better off not paying attention to that. And it's frustrating, when you’re looking at it and you’re like there's no way this could be right. Now, sometimes it is right. But if you know and can prove that it's not right, then it is not giving you the payback that you deserve.
Beth Elliott 43:36
Because one piece of bad data just ruins the whole batch. Doesn’t it?
Brandon Ellis 43:39
It’s the adage of one bad apple spoils the whole bunch. So, if you have one piece of suspect data, then the entirety of the data should be suspect. I think, largely, the industry was just tired of being talked at from a marketing standpoint, from a sales standpoint, from a promise standpoint. Everybody was going to give you the world. It was going to do all this stuff. And they always start, well nowadays, they start with beautiful dashboards, but they never get down to brass tacks of the data. We've got a podcast on that, where we went into that. I think we were already on a downward trend because I believe that a lot of people were just desensitized to that or just over it, and they were ready to spend their money on other things. That's just coming into, unbeknownst to any of us, a pandemic. During the pandemic everyone was scrambling, plants were shut down, some forced to be shut down, some having to be shut down, smaller, small to medium enterprise type manufacturers couldn’t... The small ones, especially, just had to stop because, like in the olden days when the store was closed because of the flu, you know, they got too many employees out because of sickness, and they just don't have enough people there to run the ship. So, they have to just shut down. We're just going to shut down. I mean, even the school systems initially did that, they didn't teach remote, they weren't ready for that, they just shut down. That similar stuff happened to manufacturing, and then there was this push to do remote work and try to keep a plant running, and if you didn't have those things in place, suddenly you realize “Uh, there's a lot to this IoT,” not just making business decisions but to know what the heck is going on, so I can decide where to put people and how I can do it safely and all this kind of thing. So, I believe that during the pandemic, it really bottomed out as far as spending because everybody was... It was just total upheaval, trying to decide how to keep running and how to keep moving. And then as we begin to come out of… through 2021, come out of the pandemic all the way up to these new variants, they’re causing all kinds of weird stuff now, but we began to see IoT starting to make a comeback, starting a more renewed interest I should say. Renewed interest in spending, renewed budgets, but cautious. Kind of like what we were talking about with the automation; I spent money on this, it didn't work out just like a wanted,
Beth Elliott 46:32
So, what did people forget? What do they forget? What are the most common things that you’ve seen that they forget?
Brandon Ellis 46:38
Of late or back then?
Beth Elliott 46:40
I think now would be more relevant.
Brandon Ellis 46:44
Honestly, there’s a lot of folks that are really, today, hanging on to those failed attempts. They spent that, what did you say, 200 billion? They spent their portion of the 200 billion and it didn't get them where they needed to be. Again, pre-pandemic you can say turn it off, we'll get to that later.
Beth Elliott 47:07
We’ll still have somebody go with a tic sheet and
Brandon Ellis 47:10
Yeah, we’re just going to go back to our old ways, we’ve just got production to make, we’ve got people to move. Then we went to a pandemic where just everything was in upheaval, and now they're realizing we got to get stuff back. The biggest travesty I see right now is saying “Well, we spent this huge amount of money, can we fix it?” And sometimes you just can't. We work with our customers to try to look through the bits and pieces and see what we can and can't use and we try to use as much as we can, but you have to get to the point where you ask yourself if trying to maintain this failed attempt, to keep pieces and parts, if doing that inhibits you from actually getting you to the goal that you set out to get to in the beginning, it might be time just to close the book on that chapter, and start a new chapter. And that hurts. It hurts from a financial standpoint, and certainly from a pride standpoint. Nobody wants to spend money, but I mean, unfortunately there's a lot of people out there that have purchased cars that are lemons. And they dealt with it, dealt with it, dealt with it, and finally they had to say, “I just have to get another car”. You will eat up more money trying to fix it, and it's so hard to make that determination. With a car and with an IoT system. We try our best to be compassionate in those situations, to be experts, to not be salespeople, to say I think we can use this, I think we can't, we can go about this way, and we can tie this in, and keep this part of it and but we’re going to have to do away with this part over here. Or maybe, in some cases adjusting your goal from way back is justified and can lead to some good things, so maybe have another discussion about it. But doggone it, if your goal is what you need in order to make intelligent business-related decisions, that's what you should shoot for. And as much as it pains everyone to do, you may have to just, you may have to just close the door on that, chuck it in the dumpster and say “Okay, we're going to go about it again, but we're going to go about it again smarter. We're going to make sure we don't hear what we want to hear, we're going to make sure we don't repeat the things that we repeat”. The cycle may need to take a little bit of time, you may have rushed into it, a lot of folks’ rush into it: “We need it, let's get it done, we want it on this year's budget, we got a little bit of money left”, whatever. “Let’s rush into this thing”. And that might have been the situation where you begin to start making compromise after compromise after compromise, and all of a sudden you realize you’ve got a whole pile of compromise and it's nowhere close to what you set out to do. But the money is spent. That's the thing.
Beth Elliott 50:08
So, when they close the book on that chapter…
Brandon Ellis 50:13
What do they need to look at?
Beth Elliott 50:13
Yes.
Brandon Ellis 50:14
Cyber security is the number one thing. You know, a lot of folks are pushing for cloud-based solutions and things of that nature, and that doesn't necessarily meet with all the cyber security policies of IT today. Another interesting thing is that cloud-based solutions, when they first came out, were subscription-based and some of them still are, and so that makes your initial investment more palatable. But it never goes away.
Beth Elliott 50:43
That's right.
Brandon Ellis 50:44
Now, what the industry is saying, when they look back, cloud-based solutions are the highest and most costly of all solutions compared to hosted solutions.
Beth Elliott 50:58
In the hosted you put the money upfront.
Brandon Ellis 51:02
You have to buy the hardware and things of that nature, but hosted means that it's in your plant, and you control it, which consequently is probably more secure. If it's on a cloud-based system, someone else is managing that server, you're renting server space from someone, and you're trusting that their cyber security requirements are such that the entire planet is able to see that they will stop the threats, that they will preserve your data, preserve anything that’s confidential, that's trade secret, that kind of stuff. And then that they won’t be able to jump on the line and hack their way in from outside sources as we see a lot of systems going with, on the onslaught of 3G, trying to do cellular-based systems and I talked about this in past podcasts, a lot of those systems work to, basically, circumvent or bypass the IT department, which means now there's a new vector coming in, that’s a potential cyber security issue. A gentleman once told me that there's no point in locking four doors if you disregard the fifth door that's wide open. Really there's no good point to doing that. And so cellular-based systems, if not done correctly, provide avenues for ransomware. And in 2021, ransomware has been one of the career choices.
Beth Elliott 52:44
Yeah, I’ve seen an acronym it’s RaaS, Ransomware as a Service or something like that. It’s gotten such a big business now.
Brandon Ellis 52:56
It's a huge business and for the wrong people. It's a crime. Ransomware is a crime. If you're listening to this and you think that's cool, hacking into systems and ransoming systems and demanding money, that is illegal, and it's not something you need to aspire to do. But cybersecurity is a very real thing, that's one of the things, I think, that it's according to what side of the coin you're on, whether it’s IT or OT, but cybersecurity is met differently on each side. For IT cyber security is top of their list, and unfortunately for OT, for us controls folks, we just don’t want to deal with it, we'd rather just set all the passwords to default, or remove all the passwords, or use manual switches on everything, don't worry about firewalls or anything like that, and just make it work.
Beth Elliott 53:51
That’s right. Gotta get the production out the door.
Brandon Ellis 53:55
Integration cost is another thing to think about in IoT. A lot of people they're sold a bill of goods; they’re shown that dashboard that looks so, so appealing, and then they don't delve into how you are going to get the data that makes up that dashboard. And when they find out that none of their systems on the floor are capable of giving that data, or the system that they've been sold can't connect or talk to those products or those items, be it PLCs, robots, CNCs, whatever, and then they're going to have to go out and get extra integration help to... Or it can talk to it, but the data is not ready to be gotten, it's not ready to be cultivated, harvested from the PLCs and the machine controllers. Those kinds of things are unexpected costs. And then, generally lack of standards, I mean... If you've never done something, how can you have a standard.
Beth Elliott 54:55
That’s right
Brandon Ellis 54:56
There's been a lot more experience now, and so there's people out there, like us, that can help you manage and put together basic standards. That's the other thing, 200 billion dollars, that means there's a lot of failed attempts out there. There’s a lot of successes but there’s probably just as many failed attempts, which means there are huge companies, a lot of huge companies are in the middle of all that 200 billion, and they have produced standards, but those standards are so, so, so convoluted and complex... Any SME is not going to be able to really… It’s going to be overwhelming.
Beth Elliott 55:38
300-page book of standards.
Brandon Ellis 55:41
Just working with somebody, again, if you're in our area, of course with IoT we work with folks all over the globe. We can help you put together a few basic standards to look at and to shoot for, one of those is connectivity. And then, the other thing is what you’re going to do with your data and the what-then-analogy. You know, the what-then? We didn't do a shout-out to Lisa, Lisa Richter, of CSIA, but our last podcast was a crossover. That’s what they’re called? A crossover podcast.
Beth Elliott 56:20
Yeah, their podcast is called “Talking Industrial Automation”, if you want to check that out, go ahead.
Brandon Ellis 56:28
Talking Industrial Automation, with Lisa Richter and CSIA. It's a great podcast that she does, and I was privileged to be interviewed by her and kind of tell our story. We talked a lot about IoT, because that's a lot of my background, but one of the things that we were talking about was don't be allowed to hear what you want to hear. How you go about doing that is have them prove it. Show me. We talked about vision. Set it up. Even with our robots here, we've got demonstration robot cells and things of that nature, usually we can test out the process, we actually have a simulation software for our robots. But still, you can get to the point of a warm fuzzy to know where all the pieces are coming from, but ask, show me the path, show me where the data goes to get to that speedometer needle, or that graph, or that bar chart, and then what are you going to do with it? The what-then. Lisa and I talked a bit about that. What then? And just keep what-then until you peel the onion all the way down to the brass tacks of what you really need, and then go after that. Let that be your standard. And then, we talked about connectivity. That's so big. We were one of the first ones, I think, to coin the phrase machine EKG. And so that's where we were taking sensors from machines that didn't have good connectivity capability, or maybe their legacy products and things that nature, and it just didn't make sense to buy a new machine just in order to see what's going on with the process. So, we have been getting creative since 2014 with ways to use specific sensors and things of that nature, feedback devices, flow controls, the whole nine yards, to see when a process is running or not running to maybe even check when it's down, the down time estimations, and those kind of KPIs. But also, to see if it's running the types of parts that you want. And usually with EKG method we're taking outside sensors and we're putting them on. EKG meaning we're going to see what the heart is doing without actually cutting the person open. With condition monitoring sensors and things of that nature, that stuff comes out. And that's a big trending line-item right there is machine condition monitoring, AI, and usually in the maintenance, anticipating having a maintenance or downtime, monitoring-type situation. How you utilize those sensors, though… Don't hear what you want to hear. Have them show you. Because if it's going up to their cloud-based system, if they're guaranteeing that they're going to monitor your system with their IoT stuff, and they're going to guarantee you downtime, and they’re going to give you AI to say when it’s going to shut down and all that stuff, ask them questions, hard questions. The most apparent is “What if we do have a downtime event, are you going to pay for some of that?” Is it like LifeLock where, you know, if you’re a LifeLock member and something happens to you, we’ll spend up to a million dollars or something to get your identity back and all this kind of stuff? They’re making those kind of guarantees, and the answer is they’re most likely not. The second thing is what if that does serve as an avenue for ransom and you get ransomed. Who's responsible for that? If you're entrusting them, they'll tell you. Is this secure? Why yeah, it's secure, what's the next question? You know how I know it's secure? Because it's on the sales brochure. It says secure, right here. You got to get your IT folks to chime in on that. If they say we don't feel good about this, if they say no, it's secure, you can feel good about this, okay if something happens what will you do about it? If a ransomware situation occurs, and it brings our plant to its knees and stops production, where are you going to be and if the answer is crickets, don't go there. Unless you're comfortable that you can get yourself out of that and prepare for it. That’d be the new insurance thing if it's not already there, ransomware insurance.
Beth Elliott 1:01:02
There you go. You said if anybody tells you it's 100% secure,
Brandon Ellis 1:01:10
Walk away.
Beth Elliott 1:01:12
Yeah, so how can there be insurance?
Brandon Ellis 1:01:14
Well, the whole deal of insurance is you’re betting it’s gonna happen and they’re betting it won’t. I don’t think you can give those kinds of guarantees, think it's reckless for companies to do that. I think any savvy IT person would tell you the same thing, there's no such thing as totally secure. So, I would say, keep those in mind. IoT, with your IoT, with your vision, with your automation projects, keep these things in mind, and the goal, of course, of this podcast is for it not to be vague. In other words, make it concise. Understand how it's going to work, you don't have to understand how to do it, but connect the dots. Does this make sense? And if something doesn't make sense, wait and ask the question. This doesn't make sense to me, you’re going to have to convince me of this one, this one or two things. And if it draws it out a little bit, let it draw it out. Don’t rush in. And then work with quality companies such as elliTek Incorporated, and let us help you, and help empower you to succeed. Because we'll go the distance with you, everybody loves for something to get started, but sometimes you need to take some time, evaluate, re-evaluate, everybody gets happy with it, we prove what we can prove, maybe you even need to do a paid feasibility study, it's better to spend a couple thousand dollars on a feasibility study or an engineering study, to say yes we think this will work and here's all the reasons versus most companies like us, we talk to our customers, we have those kind of interactions, and we do our best to give a quality proposal or estimate for something, and if we're selling the system or selling the components, or even helping them implement things... But if it's really critical, it's better to spend a couple thousand dollars and find out these are the things we still need to nail down before you just go ahead and hit the whole project cost a hope that you’ll get there. So do those kinds of things and take it kind of slow.
Beth Elliott 1:03:38
And I think demonstrations are always a good way of showing things, how things work. If you want to see a demo of Hanwha collaborative robot or a vision system, or the IIoTA, we can do all three of those. The email is freedemo@ellitek.com
Brandon Ellis 1:04:14
Or just go to our website at www.ellitek.com. Of course, you can always do the old-style thing, everybody's back into... I was in a Target the other day and was walking down the electronics aisle and there's all these iPods and Bluetooth, and phones, and all this kind of stuff and then a whole wall of vinyl albums, and I thought for just a second... I was like “Woah, I just went back through a time warp” because of all these vinyl albums. So, we seem to be getting back to some of the old stuff in a couple of ways, so one of those is to pick up the telephones and call us at 865-409-1555.
Beth Elliott 1:04:59
Oh, I failed to mention we do have some resources, the resource page on the website, I’ll put the link to that in the show notes and that’s a lot for the industrial robots and the collaborative robots.
Brandon Ellis 1:05:12
Yeah, so we'll build on that resource, we're building that resource...
Beth Elliott 1:05:15
The vision one, we’re going to build on.
Brandon Ellis 1:05:17
We’re trying to be empowering, to be true to our mission statement. Well guys, thank you very much for season 3 episode 3. I will say this: Keep the comments coming. We would ask that you would subscribe, if you like what you hear, ring the bell, hit the like button, give us a 5-star rating according to the platform you're listening to or watching us on. As always, give us a holler, an email, a call, and tell us about what you're dealing with, if you got something that you'd like to hear us expand upon, then certainly we'd love to do that. Beth…
Beth Elliott 1:05:56
Absolutely. Yes Brandon.
Brandon Ellis 1:05:57
We’ve rolled to the end.
Beth Elliott 1:05:58
Alright. Thank you for your expertise, as always.
Brandon Ellis 1:06:01
Hopefully it wasn’t too vague.
Beth Ellis 1:06:03
No, it wasn’t. If it was, you guys let us know.
Brandon Ellis 1:06:08
That’s right, that’s right. Alright, Beth, let’s say goodbye to these folks. See you guys.
Beth Elliott 1:06:10
See you later Brandon, and everybody.