Industrial Automation – It Doesn’t Have To…
Join us as we explore all things Industrial Automation. Brandon Ellis, owner & president of elliTek, has seen the good, the bad, and the great when it comes to automation. We'll delve into the challenges that manufacturers face, find out what it doesn't have to..., and have some fun!
Industrial Automation – It Doesn’t Have To…
Industrial Automation - It Doesn't Have To... Be Your Biggest Problem
Sometimes your biggest pain point isn't your biggest problem. There are some processes that you may or may not want to automate. Come with us as we explore those processes.
Brandon shares his perspectives, Brandspectives, on the types of industrial automation. He explains his two categories of automation, process automation and discrete automation, and why they matter.
You'll hear examples of processes that can't be automated and why.
Remember Brandon's Brandology about the four reasons to automate?
- Quality / Consistency
- Decrease Cycle Time / Increase Production
- Reclassify Labor
- Flexibility / Quick Setup
You don't want to miss Brandon's new Brandology! The top four ways to determine if an application can be easily performed by a robot.🤖 This coincides with Brandon's latest BrandRant about feasibility and beneficial ROI.
Stick around for examples of processes that can easily be automated and why.
No matter where you are in your automation journey, elliTek will meet you there!
Reach out to us with any questions or future topics.
- LinkedIn: www.linkedin.com/company/ellitek-inc
- Instagram: www.instagram.com/ellitek
- Facebook: www.facebook.com/ellitek
- Twitter: www.twitter.com/elliTek_Inc/media
- Watch👀 on YouTube: www.youtube.com/channel/UCRouULcIyr0lMNPaL4ohR4A
If you don't want to click on those links, pick up the phone and call us at (865) 409-1555 ext. 804.
#IndustrialAutomation #elliTekAutomationNation
Industrial Automation - It Doesn’t Have to be Your Biggest Problem
Brandon Ellis 0:00
You know, sometimes the biggest pain point for automating a process isn't your biggest problem. We're gonna be talking about some of the things you may or may not want to automate, and I'm going to rant a little bit. So, 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 upon 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, leave us a five-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.
So, welcome to Industrial Automation - It Doesn't Have to. I'm Brandon Ellis, your host, and with me is Beth Elliott.
Beth Elliott 1:06
Oh, that's a great opening. Thank you, Brandon.
Brandon Ellis 1:10
We’ve got some new sound effects. Brandon Ellis... So hello, Beth, how are you?
Beth Elliott 1:18
I'm doing good. How are you, Brandon?
Brandon Ellis 1:20
Doing well, doing well. So, it's getting a little chilly.
Beth Elliott 1:22
It is. I'm not looking forward to the cold.
Brandon Ellis 1:25
We’ve got through Thanksgiving. Yes. And here we are on the other side. And so true to our Thanksgiving podcast, when I said after you finish eating all your turkey, we're going to get together and talk about some automation stuff again. So that's what we're doing today. So before jumping into that, let's hit into some of the things that we've been hearing going on.
Beth Elliott 1:49
Well, I want to talk about that Hanwha is in the house.
Brandon Ellis 1:58
Southern accent, Hanwha. So yeah, what about it?
Beth Elliott 2:01
The HCR-3? The demo is here. So, Shawn can take that out, it looks like a little baby robot.
Brandon Ellis 2:11
It's actually... We are getting a lot of interest from schools and universities, a lot of the STEM type applications and then the, you know, applications with higher level universities, two- and four-year establishments, because of the size and the simplicity of it. They really are interested in the cost, but yes, being what is, is really advantageous to the academia. As far as using that in actual application, as far as the industrial setting, it could be done. It's limited reach, it’s three kilograms, so it's pretty limited payload. So, we don't often use those in those capacities, but for demonstration, and for education, it's really good. Shawn is our sales engineer for this area, and he is excited about getting out and doing that. So certainly, if you'd like to see a demo, reach out to us, contact Shawn, you can reach him through our main line 865-409-1555. And have him set up a time to come bring that robot by and let you see how it works.
Beth Elliott 3:18
See it in person. Even though it's small, it's sturdy.
Brandon Ellis 3:22
It is, it moves pretty well. Yeah. And so, you know, we have that, we have our five-kilogram demonstration unit as well. A lot of times, we use that to prove our concepts. But it's mobile as well, we can take that to customer plants to use and to see and, and things of that nature. And you know, in 2022, we're gonna be doing even more of that kind of stuff, I believe, we're gonna be doing some open houses, and of course, our training centers will be kicking back up in 2022. So, robots are going to be a big part of that and the Hanwha robots as well.
Beth Elliott 3:58
I also wanted to give an update on the FDA, the FSMA.
Brandon Ellis 4:03
Oh, yeah. FSMA, I forgot about that. So yeah, we talked about that two podcasts ago, I guess, when I mentioned...
Beth Elliott 4:09
It was the last one when I totally forgot to brush up on the rule. It stands for Food Safety Modernization Act.
Brandon Ellis 4:35
Okay. That's what it is. FSMA. So, we talked about that. And I made reference to that when we were talking, looking back at our last podcasts, which was It Doesn’t Have to be Thankless. And so, I was talking about the great research that you did for that episode. But now that's a thing now, right?
Beth Elliott 4:56
The comment period was open until January 21st. And if the rule is passed and finalized, when it is... It's two years for companies to comply to the record keeping requirements. It's still a little bit off, but people need to be prepared.
Brandon Ellis 5:16
Well, I mean, two years of compliance. That's when you have to be able to comply, but it's gonna be a process.
Beth Elliott 5:23
Yeah. And this was interesting I found. On June 1, the FDA launched the FDA New Era of Smart Food Safety, Low or No Cost, Tech Enabled Traceability Challenge. And it asks stakeholders to develop traceability tools that are scalable and cost effective. So, they are working on things that are cost effective. And I guess, you submit your ideas to them, and they'll set it up for challenge, I guess.
Brandon Ellis 5:51
That's interesting. So, when you say June, you said January, you're talking about 2021?
Beth Elliott 5:56
That is correct. Yes. So, it's still in the process. So, after two years, two years after it's finalized.
Brandon Ellis 6:03
Well, okay, so the comment period you said was January 21st of 2021. So, the comment period passed, almost a year passed. And so, then we have two more years after that.
Beth Elliott 6:18
It hasn't passed yet. And it hasn't been passed and finalized. From what I can find.
Brandon Ellis 6:22
The comment period has passed, but they still have to pass and finalize whatever, whatever they... And they haven't done that yet.
Beth Elliott 6:29
As far as I can tell, and I have looked.
Brandon Ellis 6:33
Alright, so that's FSMA. So that has to do with the FDA food traceability requirements that are there in the makings, and again, we made reference to that in the last podcast. But that was one that we looked at, in season two, the first episode of season two, which is Industrial Automation - It Doesn’t Have to be Untraceable. And that's where we're talking about the FDA.
Beth Elliott 6:57
Yes. And how is the IIoTA MES Appliances can help.
Brandon Ellis 7:02
As far as their tech challenge and stuff like that, they don't need to have a challenge, we've already done that. We can trace all that stuff; make it very easy with our IIoTA.
Beth Elliott 7:11
And it's cost effective.
Brandon Ellis 7:15
Exactly, exactly. Not a lot of engineering to go into that, you just have to be able to point and click.
Beth Elliott 7:18
I know. I can do it.
Brandon Ellis 7:23
Sorry. There you go. Little rain-type clapping. Alright, that's some good, some good highlights. So, thank you for that. So go ahead and get started with today's title.
Beth Elliott 7:38
Today's title is Industrial Automation - It Doesn't Have to be... Your Biggest Problem.
Brandon Ellis 7:45
Oh, yeah. It's for those with video, y'all been seeing it the whole time.
Beth Elliott 7:50
I know. I should do something different. And then I'll pop it over next time.
Brandon Ellis 7:55
I keep forgetting to look behind us at the backdrop, I'm still not quite used to the video. So, by the way, thanks to all those who have subscribed to our YouTube channel, and engaged with the videos we've been doing on LinkedIn and Facebook, and YouTube, we want to just let you know that we appreciate that and keep subscribing, keep sharing, we would ask you to please share if you like what you're hearing, and then follow us as well. And so, you can be updated for the latest and greatest stuff. So back to the title. So, it doesn't have to be your biggest problem. And so that's what I alluded to in the intro. So, what are we talking about there? Well, basically, we're talking about, sometimes, we are getting, a lot of folks are coming to us and asking, saying, “I want to automate this process” for various reasons. And so, we have to enter into a conversation where we're trying to discuss: is this the best? This is a good opportunity, but is it the best opportunity? Does it make the most sense for automation?
Beth Elliott 8:59
Yes. And we're going to talk about what automation is in general.
Brandon Ellis 9:03
So, what types of automation are there.
Beth Elliott 9:07
Yes. So, I want to get a Brandspective.
Brandon Ellis 9:12
Brandspectives.
Beth Elliott 9:15
So do you agree or disagree on these four types of automation. So, when I looked up the types of automation, it all comes up to either three or four. And the first one is Fixed automation, or what they also call Hard automation. What are your thoughts on that?
Brandon Ellis 9:35
Do I agree or disagree with it?
Beth Elliott 9:37
Well, yeah, because we got Fixed automation, Programmable automation, Flexible automation, which is also soft automation, and then Integrated automation. Some of these look like they blend together to me.
Brandon Ellis 9:51
Well, some of them are old terms with new words.
Beth Elliott 9:54
Okay, okay. That's what I wanted to find out. Yeah.
Brandon Ellis 9:57
So, for me hard automation is a machine or a process that's built to build one part. It's not really flexible, it's not a quick change, it's not got quick change tooling or changeover some of that. It’s built to do one thing.
Beth Elliott 10:16
Is it large batches and stuff?
Brandon Ellis 10:18
Well, that's why they do that. It needs to manufacture one part. Certainly, you want to do it consistently well, not just consistent, but consistently good at high throughput. So large batches with large yield. And, and that's just what it does. So, you know, I'll use the same analogy that I've used for our IIoTA in the past, you know, if you've built it to do one thing, manufacture one part, that's all it's ever going to do, without doing some pretty costly retooling and things of that nature. The other thing about hard automation is it may not be electrically controlled at all. It could be some of the older-type industry, what’s that Industry 2.0, I guess, not just with steam, but just mechanical automation. And so cams, cam driven, and you know, using things of that nature, where, you know, whole lines used to be just have a common shaft, and it was being turned, it may be connected to the water wheel or steam engine or something, but this whole shaft is just turning, and then different processes down the line would have belts that would come off that shaft, based upon the pulley side was would decide how fast the opposite end of that shaft was turning for that process. So, they could tune that process to get the timing right, so this continuous process could be just shaft driven all the way down. And then those things could turn cams, cams are like a lobe on a shaft. So as it spins, things go out, and then they go back in, and just like a cam in an engine that adjust as the engine turns, the crank turns, there's a cam that turns and that cam is deciding, it’s controlling the valves opening and closing, and the crank is turning the pistons, and so the pistons have to be in a certain position before... certain valves have to be in a position relative to that piston and things of that nature to do your cycle of a combustion engine. That's all mechanical. Now today, we have more electrical control in an engine. But if you go to old school engines, we're talking about, you know, engines, probably 1960 and before, certainly you get back in the 1900s, the old model T’s and things of that nature, you know, once that engine started, it's a complete mechanical process. Now it's electrical as far as spark plugs. But that's even being driven based upon mechanical things that are turning and spinning and creating that spark. And so that, to me, is hard automation, as far as older type means of automation. But even with electric, you can be doing high speed motion, you can be doing all kinds of things. But if that machine is built to run really one specific part and do that very well, very quickly, then that's what I would refer to as hard automation by today's terms.
Beth Elliott 13:23
Okay. And then Programmable automation is obviously using programs.
Brandon Ellis 13:28
Well, and even program automation, you know, you can... So hard automation to me, the way I see that is more mechanical, mechanically driven, mechanically timed, just mechanical. When you get into programmable automation, now we have something that we can change a program on. On a mechanical, you can change the program, you just have to machine a new cam. So, if you want something to go faster, or whatever, or move further, you just machine a new cam, go in there and mechanically take out the old cam, put a new cam in and now that'll follow that motion. So that really is programming, right? Because we're changing the way the machine runs the timings and things of that nature. So programmable automation, the way I compartmentalize that is it's something we can program certain things, but we can't add anything to the system or necessarily subtract anything from the system. So mechanical items, well mechanical meaning things you can hold in your hand. That includes sensors and things of that nature. So, if the machine is the way it is, I can go in and change certain things like I could change a timing sequence, I might be able to even change the speed. But I can't add features like monitoring, you know, I'm going to change the speed based upon monitoring, you know, flow or monitoring temperature, something like that. I can't do that because I would have to add something to monitor the flow or monitor the temperature. And so, when you're talking about specifically programmable automation, I don't know how useful that is, but maybe it is. Imagine being able to go in and well, your toaster, we used toaster before, I was gonna say the toaster is only going to ever toast toast. That's what it does, toast. It's not gonna wash your dishes, it's not gonna check your email. Who knows nowadays? Internet of Things we're making refrigerators email you, maybe toasters will too, I don’t know.
Beth Elliott 15:27
Text you when your toast is done.
Brandon Ellis 15:30
But you got a dial on or some kind of way of saying I like my toast more toasty or less toasty. And so that is changing, probably it's a thermostat setting that says at a certain thermostat setting, we're gonna pop this thing through well, however the magic is, that comes to pop your toast up. But you know, just make it stop baking. But that's where you have to have that capability. So that is programmable, you can go in and program your toast to be different from when I do mine, I can change it, right. So that would be an analogy of programmable, meaning, you can't do anything else, you can't, you can't change the force by which the toast comes out, you can't change the size of the toast that's going in to where you can do a whole loaf of bread instead of just a slice. You can't change those things, the mechanical aspects of it, but you can change how long it stays in. And so, you have the ability to program that. And so programmable automation means that all you can do is program what you have access to. The next one you mentioned was...
Beth Elliott 16:42
Soft automation or flexible automation.
Brandon Ellis 16:45
And now all of a sudden, that's when we can start pulling in... Again, these are my interpretations of those, this is where we’re going to start pulling in both the controls and the programmability with the ability to change things. So, we may do a quick setup, so maybe we have linear actuators that change the size of you know, the size and shape of the parts, maybe you have mechanical stuff, but it's quick change. So, you can do quick change tooling, quick change fixtures, things of that nature. And then you can adjust programs so that when you're running this fixture, or this set of parts, or you're adjusted to accept this part, the program runs totally differently, then when you’ve got this other part in there, you know, instead of all 10 steps, it's only going to run 3 steps or you know, and they're going to change their cycle times and things of that nature, we could do those kinds of things. And you can also begin monitoring stuff like, I don't know, if you need to monitor a tank level. For this part, you may need the tank to fill up to flow so many gallons of water or whatever. But for the other part, we need half that or more than that. So, you can monitor the flow, or you can monitor the levels, and the programming can come into play. But if this part needs 10 gallons of water in the tank, and you only have a five-gallon tank, it's not gonna work. So, you may have to change out the tank. But if you change out the tank, and you know, that's a quick and easy thing to do, then now it's flexible. Okay. So quick change tooling and that kind of stuff comes into play.
Beth Elliott 18:17
Okay, what about the integrated?
Brandon Ellis 18:18
Integrated means we're just going to take a lot of little stuff and make it all work and do one kind of centralized control system over on top of that. Now, traditionally, we've used SCADA systems, I guess for that. Or you could do a centralized PLC system, we do centralized control, there's an age-old question of centralized control from a PLC standpoint, one PLC controlling many, many processes, or having a lot of small PLCs controlling their specific processes, and having them report back to a supervisory control.
Beth Elliott 18:50
Okay, okay. And I bet there's some, give and take with both of those.
Brandon Ellis 18:55
Well, there is, you've got a communication and then also, what if you start getting... if everything's a PLC... Or even better. Let's say everything is the exact same brand of PLC. Is that reasonable? No.
Beth Elliott 19:06
It seems like it'd be expensive.
Brandon Ellis 19:09
I mean plants, you know, most plants, most manufacturing plants of various sizes are trying to have standards and things of that nature. But sometimes, especially for the small to medium sized manufacturers, if you've got a piece of equipment, and it has an older controller on it, or some other brand of controller, but the machine works fine, there's no reason to budget in retrofitting all that and getting, you know, ripping it all out and trying to put new stuff in just to match your standard. Or maybe they don't have the standards as close as possible. They're just really about trying to make production. And so, when you start having all these dissimilar systems and legacy systems and trying to pull that together. Now, if you're using the IIoTA, no problem. I mean, it’s according to what you’re doing. We control traceability, or we control process workflow. But we’re not going to control a machine, we're not going to do logic. We don't do ladder logic per se. But if you need that for your setups to get something from the ERP system, or even a cloud-based system, if you're going there or whatever, I mean, we can deliver that stuff very easily. All you have to do is point and click. But and so we take the place of some SCADA systems. So, what SCADA stands for, acronym SCADA.
Beth Elliott 20:39
Supervisory Control and Data Acquisition.
Brandon Ellis 20:42
That's right. So. So supervisory control, that's a centralized control system, and data acquisition. So that's what the IIoTA is going to do. It's not really going to give control as far as being able to push buttons on, on the front of the thing and change, you know, actually be like a human machine interface. Those machine interfaces are down there as the way we would say, or they’re somewhere else. We're not a replacement for a SCADA system, I guess that’s what I'm getting at, with the IIoTA. Well, sometimes it goes under it, sometimes it goes over it. Our job is to move data to and from the enterprise systems and the operational systems, OT operational manufacturing floor. And so certainly, we could do that. But the point being, that for integrated automation, being able to, as an example, let's say you've got, you know, if everything's a PLC, that's great, but what if it's not? What if it's a CNC controller? What if it's some brand of robot, you know, a Hanwha, or something like that? What if it's on the certain parts of the process, you know, it may be a PLC, it might be a PC based system, you know, all these different things that are taking place down the process, down the manufacturing line. Or the process may be on one side of the plant, and now we got to bring parts that are manufactured over there, sub-assemblies and bring them over to the main finished final assembly area and start putting them all together. So, we need to make sure that all the stuff that took place here is known here. Because if there was a bad part made here, we don't want to run that bad part in final assembly. We don’t want to spend the energy, the money, the material, the labor. And so that type of stuff is integrated automation to me. And that's even on a larger scale. That's probably more industrial automation integration. But the most basic, probably, what the internet would say the most basic version of integrated automation is just making robots and CNCs and PLC based systems all work together.
Beth Elliott 22:52
Okay. What are Brandon's two categories of automation?
Brandon Ellis 22:58
Well, there's really two, if you boil it down, we talk about... Well, there's probably three, I mean, machining, you know, so what we call numerical control or CNC type stuff. So machining is kind of its own island. And more and more, we're working with machines, especially when we're doing machine tending with robots so that we're communicating with them. But they kind of have their own world. They use, if you're traditional, if you're a new student coming out of college, then they've told you, you know how to program CNCs, and if you're a veteran CNC programmer, you’re shaking your head back and forth saying they don't know anything about that, because there's a thing called G code. It's a programming language, G codes, M codes, things of that nature. That's how we program CNC machines or numerical control machines, Computerized Numerical Control, it's an acronym, CNC, so Computerized Numerical Control. And so, it's kind of its own thing. So, I'm not really including that. But even then, there's really two basic categories of automation, there's process and then there's discrete. And so, a process in automation is automating a process, and really, I always say, that's what the chemical engineers are doing, right? So, if you're in a chemical processing plant, or, even if you're in food, and you're mixing foods and things of that nature, you're controlling more of a process there. Yeah, there's discrete parts of it, where we're opening and closing things and turning on motors and turning off motors. But we're doing it in a way that we have to do everything kind of ques off of everything else. When you're baking a cake or when you're putting together the recipe for a cake. If you put too much flour in, if you put too much. I don't know what goes into a cake. It might all come out of a box.
Beth Elliott 24:53
Some do. Well, you still have to put eggs and oil in there.
Brandon Ellis 24:57
So, if you put too much oil in or not enough oil or you missed the eggs or whatever, the eggs aren't right or something. So, in a process now imagine a large company, a chemical company or something like that, if they're doing processing, they're gonna be monitoring flow. They're gonna be monitoring, probably temperature, you know, that kind of stuff. And we use things called PID loops. So proportional integral and derivative gains. That's what we're using. That's how we decide a process. That's how we engineer a process. And so just a quick example on that, why would you use… What's the difference between PID temperature control versus discrete? So discrete is off or on, zero or one. There's no in between. And so, my stove, my cooking stove at home, it's electric, and when I turn the eye on, I see the eye come on and it glows red. And then after a few minutes, it clicks off and it fades away. And then just a few seconds later clicks back on and comes back. And then when I turn the temperature down, if it's glowing red it clicks off, and it takes even more seconds before it clicks back on, because it's waiting until the temperature comes back down. But it's still a discrete temperature control, that eye is just turning on and turning off. How long it stays on and off, can be adjusted. But you can't say turn halfway on, or only use 30% power or 60% power. It's 100% or it’s off. So, it's discrete. If it was being controlled by a PID, it would be not that way. It would be okay, we're going to turn you 100% as long as the temperature is far away, as your temperature starts approaching your setpoint, your goal, we're not going to wait until you get there and cut it off.
Beth Elliott 26:49
Because then it'd be too much.
Brandon Ellis 26:50
Yeah, because you're going to overshoot. So, we're going to control that. And we're going to start easing back the power and easing back the power. So, we're trying to get that control temperature, you know, the target and the control, trying to get them to come together and just roll off and boom, there you are. Trying to do that in the shortest amount of time. But we don't want to overshoot and then come back down. It just takes longer. And if you overshoot baking a cake, I don't know what will happen to the cake, but it may not be as good and certainly not gonna be as consistent. So that's the kind of stuff that process automation is. And then there's deceit, I'm sorry, discrete automation. And that's what most machines are. That's where we're doing discrete functions, we've got a PLC involved, we may still be doing some temperature control and stuff like that, but that's not the crux of the entire process. We're usually making something or doing something to a part or something. We've got air cylinders that are firing. We got electric cylinders that are moving. We may have some motion going on. There various things may even have robots, but it's very discreet. You can write that down a process, you're going to turn this on at this, you're going to run this process when this process is done, you know, we're going to do this, we're going to fire this, this valve, when we see this sensor showing the grippers open, then we're going to take the next step, we're going to turn it off at this point. We're not squeezing to a certain pressure. We're not doing anything in between; it's off or on. That's discrete manufacturing. And that's what most general manufacturers are doing.
Beth Elliott 28:23
Would those types of automation, the fixed, the programmable, flexible...? Would those fall under the discrete or is it just mostly I was trying to categorize it too much?
Brandon Ellis 28:37
No, no, I think most of those are going to be discrete. Okay. Especially the fixed. Well, the old timey fixed, because if it's all mechanical, you're pretty much getting what you’re getting. As you get into more flexible automation, again, we can be doing that kind of stuff, it really, I don't know, it comes down to most of the time, when I see process automation, I'm seeing all of these PID controllers or temperature controllers and flow controllers. They may be, you know, basing it on pressure levels, whatever. And they're controlling various things. But they're controlling them somewhat. They're analog, not digital, digital is zero or one, discrete and digital, same thing. Analog, I've always said, the brain, the brain of the male, the human male, is discrete. The brain of the human female is analog. Because with us men, most of the men, I’m gonna say with me, it's either on or it's off. It either is true or it's false. It's black or white. And with my wife who I love to death, it's not. It's kind of on or kind of off or it's, that's kind of yellow, it's kind of not. You know, and for me, you know, I've got ROYGBIV. I've got the five primary colors, and I don't have cauliflower and all these other crayola colors in my book. It’s just boom, that’s what it is. And so, for me anything that looks blue is blue, and anything that looks green is green. And that's it, there's only green and blue and ROYGBIV, red, orange, yellow, green, blue, indigo, violet, how about that, ROYGBIV. But, you know, that's a very discrete way of thinking. The analog way... And just like with processes, discrete, bam! Turn it on, turn it off. We're just firing valves, we're moving to positions, that kind of thing. Process Automation is more about moving it into where it needs to be to be perfect. And so, because you’re engineering a process, you're doing batches, you're doing things of that nature. So, if we're making a tablet, you know that it's going to be medicine that you're going to put in your mouth or give to your children or something like that, we want to make doggone sure that when that's put together, as the chemicals that we're putting there are, are weighed out. And as they're administered and everything before it ever gets made into a capsule, or a caplet, or a pill, we want to make doggone sure that those are dead on. That is process. That's where we're auguring out, or we're feeding out material. But at the same time, if you're talking about powdered drink mix for your water, if they add a couple extra grams of crystals in that packet versus if they don't, it's not life threatening, so that's what I would classify that as more, it can be more discrete. But if it's medication, we need to monitor the batching of that, especially, you know, if we're making chemicals that we're using for, I don't know, cleaners or whatever, chemical processing, where we're mixing chemicals, we have to monitor those flows, we have to, if we're having a chemical reaction that takes place, that comes with temperature, that comes with pressure, it comes with all these different things that have to happen, you're cooking something or boiling something, or something like that, you have to make sure your temperatures are maintained, and they need to be maintained perfectly and consistently, and those kinds of things. Even with food, we had a customer that what they do is they process food that's going to become TV dinner. You're going to get it out of your freezer, and you're going to heat up, which is quite common for me. That's my cooking.
Beth Elliott 32:38
You add to it, though.
Brandon Ellis 32:39
Take the nutritional information and throw it out the window when I’m done with it. But that food, it can't be bad, it's got to last. And we don't want just pack preservatives in and so they've come up with some clever ways of, of going through and doing all the things that I don't know about, you know, pasteurization and all this kind of stuff to where they, they can get the food in such a way that it can be flash frozen, and then when you heat it up, it's just as good as the day it was cooked. And it's not packed full of preservatives and all this kind of stuff. And so, to do that, their process has to be that they do that under pressure, they do it under temperatures, they control temperatures, pressures, flows, all kinds of stuff, to make sure that as this food packet is going through this process that everything's where it needs to be. That is process automation.
Beth Elliott 33:37
All right. So, what are the hardest manufacturing processes to automate?
Brandon Ellis 33:45
Well, I think that comes down to why you're automating. Brandology. We've been talking about this for, I guess, since the beginning of the podcast, Brandology. Four reasons to automate: quality/consistency, decrease cycle time, reclassification of labor and flexibility/quick setup. We may need to add a fifth one, I had a conversation the other day with a customer. The reason they wanted to automate was they were concerned about the operator's safety. So, they felt like if they can automate this process, it will be a safer process. And I'm not sure where that would fall under.
Beth Elliott 34:28
Reclassification of labor? It could, because you're trying to take the labor off that.
Brandon Ellis 34:35
But in that case, I mean, reclassification was going to happen anyway. But the crux was because they were concerned about the safety of the operator, because the process had changed a little bit. It wasn’t quite as safe a manual process as it used to be. But anyway, so those four things. I would say it really comes down to why are you automating? It's got to be... It doesn't have to be one of those four, but I mean, it can be more than one of them, multiples. But one needs to be your primary goal. And so, which is the hardest? I think we need to add a new list.
Beth Elliott 35:17
Okay.
Brandon Ellis 35:21
Brandology, different list. So, let's call it the, the top four ways to determine if a process is worth, you know, trying to automate. Let me back that out a bit and make some explanation there. The majority, so what's trending? The majority of what's trending right now in our world is automation. But more specifically, just put a robot on it. And when they're talking robot, they're talking articulated arm, six axis, five, six axis, articulated arm robot. Just put a robot on it. And it may be industrial, may be collaborative, but just put a robot on it. And it makes a lot of sense. If you got a six-axis robot, you've got some things that you can do. But...
Beth Elliott 36:12
You have to be realistic, don't you?
Brandon Ellis 36:14
You kind of do. And so, some of the stuff, and we talked about this, we've talked about this before. And when I talked about the wiggle jiggle, there are some things that a human can do. And I'm not talking about things that a human can do, like you know, being a slalom skier or something like that. I'm talking about the nuances that you didn't even think about. That you just do. You don't really, you don't realize you're doing it. The wiggle jiggle is one of those. What the wiggle jiggle is, is in this case, I was watching... A customer wanted to automate a process, it was a machine tending process where we were, it was a CNC lathe, and so the lathe would do its thing and trim down the part, and it was a finished part, and it was ready to be taken out. And even though the chuck would open, the part was stuck in there just a little bit, a little bit of stiction and the operator reached in and kind of twisted his wrist like for riding a motorcycle, kind of did a little quick little twist and pull at the same time. Twist and pull, wiggle jiggle. He kind of moved it and got it out of there and it broke free and he pulled it out. He said we want to automate that process. I said how often does he have to do that little move there, the little wiggle jiggle move? Sometimes he does, sometimes he doesn't. Well, the robots either got to do it all the time, or none of the time. If the robot does it all the time, and trying to program in wiggle jiggle...
Beth Elliott 37:50
Oh, goodness gracious. I couldn't imagine.
Brandon Ellis 37:52
Yeah, I mean, because there's a feel to it. Right? So, you know, the human brains got... You’re feeling you got it, you got it, you can feel what's happening, you can feel when it breaks free and things of that nature. You can see it, you know, you got all these senses. And so those kinds of things. So, I've come up with a new list, the top four things or top four ways to determine if you have an application that's worth automating, if you're talking about just putting an articulated arm robot on it. So, if you're unsure, and I think that's what we've got. So, the hardest, and the question was, what are some of the hardest manufacturing processes to automate? It's hard to classify that.
Beth Elliott 38:37
Well, the internet, it was like, what was it? Material handling and final assembly. From what…
Brandon Ellis 38:44
Yeah, but sometimes material handling is a no brainer. So, how can you determine that? Okay, so here we go. The top four ways, if you're struggling with that, put mittens on it. If you have an operator that's doing their stuff, do you know what mittens are? Yes, they're not gloves.
Beth Elliott 39:06
I should have brought one. Your four fingers are in one piece and your thumb’s in the other.
Brandon Ellis 39:15
So, you only have two appendages. Okay. So, if you can put a mitten on your operator, and they do it, they can do it. They can still do the process with no problem. That's a good sign.
Beth Elliott 39:26
Okay. So as long as I can go like that.
Brandon Ellis 39:29
Like crab claws. Number two: Tie one arm behind their back. Okay, we're talking about one robot, not two. Now granted, we have Motoman robots, and they have their DA, their dual axis, that has two arms, dual arm. And it's really cool. It cost more. You know why? Because it's two robots. So yeah, tie one hand behind your back. So, you can't use two hands. Even if you have mittens.
Beth Elliott 40:04
So, if I have a mittened hand, just one mitten hand...
Brandon Ellis 40:06
That's right. One mitten arm.
Beth Elliott 40:11
Okay. Because you still have your arm
Brandon Ellis 40:13
Mittens on your hand, you still have your arm, because a six axis articulating arm robot works similar to a human arm. And that's what most people are thinking is, they’re watching this person do this stuff and they’re thinking, this is no problem, okay? But sometimes it is. So put a mitten on them and tie the other hand behind their back, because sometimes they'll inadvertently reach up, take this part and hand it off to the other one. And in doing that they change. They're doing a passover of parts. That's one thing. I mean, even between two robots.
Beth Elliott 40:44
You have to program each one of those moves, don’t you?
Brandon Ellis 40:48
All of that needs to be programmed, yeah. And then put a blindfold on them. Now, I mean, we're getting down to the basics here, if they can put a mitten on, tie one arm behind their back and put a blindfold on, and then one last thing, their feet are planted on the floor, they can't move.
Beth Elliott 41:06
That's right. Because unless the robots on something.
Brandon Ellis 41:12
Well, you can do that.
Beth Elliott 41:14
Now you're getting into other costs, sorry.
Brandon Ellis 41:15
Now you’re getting into more cost; more complexity. So, so many times, especially in the last few months, with labor shortages and things of that nature, we are blessed to have many, many opportunities to go out and talk to folks about how we can use a robot to automate this process. And the first thing, now here, we're gonna rant. I mean this is my rant.
Beth Elliott 41:34
Brandrant
Brandon Ellis 41:35
The first thing they go to is ROI. And they base that up on this is our biggest issue, this is our biggest problem. And if we can solve this all and it's like, we win the lottery, right? And, of course, we want to, we want to help you with that. I mean, of course, we want you to win the lottery. But when you start looking at those processes, you can automate, I've said this forever, you can automate anything, if you have enough money, enough time, and enough patience. Money, because it's gonna cost, sometimes it's gonna cost a lot. Time because the more complex it is, the longer it takes. And patience, because the more complex it is, the more you're going to want to pull your hair out. I don’t have that luxury. If you want to look at something in the plant, especially now where most people are looking for, because they're focused on ROI. You know, I go back to an analogy of a report, and this is an IoT related analogy. But we had a customer, it was an IIoTA user, they are an IIoTA user, they wanted at first, “help us, we want to know all the downtime events, just a count of downtime events”, and they would keep up with what kind of downtime classification it was. But what's the total number, so they created this, and we helped them create this report that said, for this, on this line, and all these processes, you know, through your entire processes through your plant, from soup to nuts, these processes, at each one of these machines, they even got that granularly, down to where this type of event or this type of event we keep a count. So, they had this graph that showed their top four, highest downtime events, just by the number of occurrences. And there was one that, you know, number one, and then number two was slightly behind it. And then number three was way down, you know, pretty pretty far down as far as number of occurrences. And number four, almost didn't make the map. I mean, it just didn't happen often at all. And so, they were doing all of their capital expenditure, all their focus, they were talking about bringing in all these folks and machine builders, and that's why, you know, we were there to help consult and that kind of stuff. How can they reduce on this number one column the number of downtime events? Well, as we worked with them in a consultive way, the question came up, how much downtime does all this equate to? And they said, “well we really haven’t looked at the downtime, the accumulated downtime for these events”. And so, they started, you know, they had the IIoTA so that was an easy thing. So, they did some pointing and clicking and created a new graph that showed total downtime for each one of those accumulated processes, or downtime events. And they laid them on top of each other. And it told a totally different story. What it said was the first category and even the second category, but the first category complete with all these occurrences, the total downtime was not even in the top four. So, it was happening a lot, but it didn't take long to fix. Then you get down to number four that barely showed on the map, barely showing how many downtime events, but to fix it, you measured in hours. So suddenly, your amount of downtime that you actually realized, from your least squeakiest of the wheel, is where you should be spending your money. The same thing should apply to: what we are going to automate? So before you jump into doing all the steps, to say, this is what we want to focus on, we want to bring in an elliTek, show us, help us, consult with us, help us to automate these things, I would suggest use these new four ways, four reasons to decide if you know, an articulated arm robot or some type of automation is going to be feasible. And if it passes that test, then use that to set up your two, three or four, you know, potentials, and start your ROI analysis and feasibility studies on those. That will give you the shortest term, highest return. Now, it's not going to win you the lottery maybe. But let me tell you something. What they realized was, if we spend all this money on what we were originally going to spend money on and we realized a 10% improvement on downtime, their total downtime was like less than 15 minutes, so 10% will be 1.5 minutes of improved downtime. The other one was measured in hours, which I think it was close to getting close to two hours of downtime. So that's 120 minutes. So now 10% yields 11 minutes of improvement. It's a much better payback, because that's 11 minutes added to parts going out the door, and it’s the gift that keeps on giving. And so, think the same thing. So let me review those again. Put mittens on it. Tie one arm behind the operator's back, put a blindfold on them, and tell them their feet are tied to the floor, they can't move. Now, how do we get past that? So, if you want to, if you can't put a mitten on it, we've got to get more expensive grippers, okay, maybe even grippers that are more analog than discrete to where we can do pressure based, gripping and things of that nature.
Beth Elliott 47:33
So, they can tell how, how much pressure when they're picking up something.
Brandon Ellis 47:37
That cost more. The second thing, tie one arm behind its back, maybe we need two robots working together. That's more programming, more engineering, more cost, more time. Blindfolded? Well, if you need to see, we can do vision systems, we can even do 3D vision systems, but they cost. And there's a complexity with it. Vision systems themselves, we can set them up in the lab environment to work perfectly. But as soon as you move into your plant and the light changes, or you upgrade lighting in the place, or you add a skylight or move, you know, open the window, pull the drapes back, whatever, vision systems, vision guided robots can need constant supervision. They can need maintenance or management. And then standing in one place, a lot of people are pushing for what we call the seventh axis, six axis articulated arm robot, we stick it on a thing that moves, or an AGV. Now the AGV is still new. They're neat. They are pretty cool in the way that they work. But they're not 100% accurate. So, if you move a robot up into a position in front of a machine, realize that it's not going to stop in the same place every time, every single time. So, it's not going to be the same thing as having, well, you know, having a robot that can be nailed to the ground, and always reach into the same spot. If it moves up, we’re going to have to do things to try to figure out where we are and adjust our user frames and things of that nature. We can do that but there's more cost. So that's the thing that I would get to. So many people will come to us and say, we just walked through the plant, we looked at this, we noticed we didn't think that was a very hard one to do. And so that's when we want to automate. And we start kind of, we’ll have to overcome this, we’ll have to overcome this. And you can just see them kind of sinking down in their seat. Because they're like, “oh, that's, that's yeah”. Or they'll come on out and tell us. This is our budget, we feel like we can do this, you know very, very well and get a six-month payback or something like that. I want you to have the six-month payback. But if you overlook some of these little nuances, it can bite you and it can knock your budgets way out.
Beth Elliott 49:58
Yeah, yeah. So is that like the Rube Goldberg?
Brandon Ellis 50:03
You don't want a Rube Goldberg machine. I've seen some of that. Rube Goldberg machine for those of you who don't know, Google it and get on YouTube and watch some videos because they’re fantastic things. Yeah, you know, Rube Goldberg is all about timing. And everything's got to be consistent. And you know, you're relying on all these other things to happen, just to make a certain outcome. But there's a lot of opportunities for failure.
Beth Elliott 50:28
Yeah, because there’s a lot a chance in there.
Brandon Ellis 50:31
There’s a lot of chance. Everything's gotta be aligned perfectly, and things of that nature. And I have seen those types of moves from equipment, we've never done it, we try not to. But you know, just seeing some… if it works, we call it clever. If it doesn't work, we call it dumb. Right? So, you're gonna go one way or the other, but you don't want the Rube Goldberg machine. So, what are some examples of processes that can be automated? Well, we've actually been talking with some folks about polishing, deburring, and things of that nature. The interesting thing there, I would say, is think about, do you want to bring the part to the process or the process to the part. And not everybody thinks about that. Sometimes it's easier to take the process to the part than the part to the process. But when an operator is doing it, a lot of times, they're taking the part to the process every single time. It's according to your situation, what you're dealing with. But sometimes it's easier to bring the process to the part. So instead of taking a part with a robot and moving it up against a polishing wheel, it may be easier to attach the polishing wheel, you know, whatever you got the grinder, the deburring unit, whatever, to the robot, and let it come to the part and do stuff to the part while the part's fixed. Let's see material handling. You mentioned material handling, the internet said it was tough.
Beth Elliott 51:56
Yeah, yeah. You think it's an easier one?
Brandon Ellis 52:01
Material Handling is probably what most robots are doing. Saying material handling is so generic, though. That's like saying math is hard. I mean, if you're talking about simple addition compared to complex, you know, algebra and calculus, or trigonometry or something like that where you're doing fourth or fifth or 100th degree integrals and things of that nature. You know, no, you can't categorize math as hard. Some math is hard. Some material handling can be hard. If you're not sure, apply these four things, and then you won’t have to worry about hard. If the answer is “well, we can't do it with mittens, and we can't do it. No”. And then you know, if you can do some of those things, maybe, but you're getting harder from that point forward. If you, just like even if we had, you know, 3D systems with seventh axes, and two or three robots, and the best, you know, most expensive ambidextrous type grippers, human hand grippers, this still will be hard, then don't, let's not automate that one. Let's use a person. Sometimes you just need the touch of the human touch. And so that kind of thing. But so, material handling. And then of course, we always do dispensing and inspections. So, dispensing would be gluing, caulking, something like that, where we're moving in a pattern. That's real good with robots, even cartesian robots, we do that a lot with, SCARA robots, and not even dispensing, we can do cutting. The ultrasonic cutters and things of that nature for cloth material. Ultrasonic welding, we do that a lot with SCARA type robots and cartesian robots. But then inspection means you just got a camera on the end of the robot, or you're moving the part in front of a fixed camera. Again, do you take the part to the process or the process to the part? Those things can or cannot be interesting. A lot of those things you can prove out too. That's why we have, that's why we keep robots here.
Beth Elliott 54:09
Yeah. Can we show a video?
Brandon Ellis 54:11
Absolutely. Wanna see a video? So, here's one that we've got set up. This is actually a proof of concept for a customer, actually it is more than a proof of concept. They're actually doing it. So, this is one of our Hanwha robots, collaborative robots. Now why do we have it guarded or guarded? I'll tell you why we have it guarded. Because it's moving faster. And you look at the end of arm tooling. Bring up that gripper, can you bring us onto that gripper? So, we're grabbing from the inside. So, we're catching the part from the ID, the inside diameter of the part with those grippers. So that's why they're spread apart right now. We don't have parts in this video because number one, they're confidential but also, we don't have any just because. But that's what the tooling is supposed to do. But you can see that tooling has sharp points on the edges. The gripper has sharp points on the edges. For those of you who are collaborative folks that think, yeah, just tell everybody to get out of the way, we don't need any guarding. Imagine how slow we would have to be going to keep that in the collaborative realm as far as the pounds per square inch with those points. Now, if we had designed some kind of shroud around it, and everything that also housed the part, those kind of things, we could possibly do it. But in this case, doing all that design and everything. We looked at the feasibility of doing that. And then the cost of just a couple pieces of extra extrusion and some finger safeguarding, it was a no brainer. So that's the kiss, you know, keep it simple, stupid. And so that's what we're doing. Go ahead and play that again. So, it's moving pretty, pretty thoroughly. And what this is emulating is picking a part, machine tending, we're going over, we'll be going over, they'll be, the customer will be going over and doing a quality check. And then based on that quality check, it'll either pass or fail. And it'll either be like down the good chute or placed into the reject chute. And so there it is, right there. Pretty cool. Yeah. So, there you go. That's a good example of material handling.
Brandon Ellis 56:34
So yeah, I wouldn't say that those things are too, too hard to do, necessarily.
Beth Elliott 56:40
Okay, so what advice would you have to share with people?
Brandon Ellis 56:45
Well, again, I think these four reasons, and I've put some thought into this, as we've gone through the, you know, the mittens, the blindfold, the stand in one place, the one arm behind your back kind of thing. I'm sorry if it's rudimentary, you know, I apologize for that. But I think that it's a...
Beth Elliott 57:02
I think it's a good, easy way to remember too.
Brandon Ellis 57:06
It is, and it just brings everything into perspective pretty quickly. Yeah, and kind of kind of helps boil that down. So that saves you some time on that. That's the great thing. You know, and then you get on to your other reasons to automate, your other ROI calculations as far as you know, this is, you know, looking at the high-volume tasks and the impacts, you know, on the systems, the compliances, the audits, you know, audit requirements, those kinds of things come into play, and general ROIs. I mean, the rest of that feasibility study. What I'm seeing a lot, what I've seen more often than not, in the last few months, is folks are trying their best to find a way to get to an ROI, and they're pulling potential automation projects based upon ROI. And thinking this, if we can do this, you know, we'll get the highest ROI. But it becomes so complex and whatnot, it blows their budgets out of the water, what they're really budgeting for. And so, if you can pass this through this initial filter first, and then from that, from what falls out of that, now start doing your ROIs. The benefits will be, in less time, be shorter. They'll be, you know, the ROIs, again, you may not do away with, you know, we don't even need to have half of the plant, we can lease it out, you know, whatever, you know, it's not going to be that. It's not going to be lotto. But it's gonna be something. And it might be a lotto like, because now all of a sudden, with the same budget, you may be able to say, with what we would have spent to automate this one process, we can now automate three or four processes. And when you add those up, it equals with this one, is, except with, you know, a lot less complexity, a lot less money, or, you know, the most money's been spread across, amortized across, and a lot less time. And a lot less frustration. So, less frustration equals no heightened need for patience. So, there's plenty of reasons to be frustrated these days and times, let's not make automating a process one of them. So that'd be my advice.
Beth Elliott 59:25
Very good advice.
Brandon Ellis 59:25
So good discussion today. It went a little long today. So sorry for the long podcast, but we're talking about some cool stuff.
Beth Elliott 59:33
Well, the one before was so short.
Brandon Ellis 59:35
We’ve got credit. So, guys, thanks for joining us today. Industrial Automation - It Doesn't Have to be Your Biggest Problem. There it is. So, we want to invite you to, again, share, share our videos, share, share our podcast. Certainly, give us your feedback, leaving comments. Subscribe, give us the five-star rating, like our videos and our podcast that helps us to continue ahead on the search. Certainly, check us out across all those latest and greatest podcasting. Whatever your podcast tool is, if we're not on it, let us know.
Beth Elliott 60:18
Please, because I've not done my job.
Brandon Ellis 60:21
And I would be quite surprised if that was true. Because Beth has done a fantastic job and getting us on all that. And then of course on social media with Instagram, Twitter, LinkedIn, and Facebook, and YouTube. And so certainly continue to listen, listen and watch us and as we go forward. We've got some new topics all in the makings, lined up. Yeah, we're gonna be talking about some really cool things. But I hope you survived your Thanksgiving. And hopefully now you're dialing into some things to automate. So, if that's the case, please we invite you to give us a call at 865-409-1555 or check us out online at www.ellitek.com. And certainly, check us out on social media. That's right. So, Beth, have a wonderful day.
Beth Elliott 61:19
You too, Brandon. Thank you all for listening and watching.
Brandon Ellis 61:22
And watching. That's right. We'll see you.
