Chris  0:00 
Welcome to EECO Asks Why. A podcast that dives into industrial manufacturing topics and spotlights heroes that keep America running. I'm your host, Chris Grainger, and on this podcast, we do not cover the latest features and benefits on products that come to market. Instead, we focus on advice and insight from the top minds of industry, because people and ideas will be how America remains number one in manufacturing in the world.

Welcome to EECO Asks Why. Today we're going to be having a fun idea conversation, and we're gonna be talking about industrial IoT. And what does that mean for industry? So helping us with this conversation is Amos Purdy, who works for Global Process Automation, as a Lead Systems Engineer. So welcome, Amos.

Amos  0:46 
Thanks.

Chris  0:47 
Hope you're doing well today, man.

Amos  0:49 
Yeah, yeah, sun's shining.

Chris  0:51 
Well good. The sun is shining here also. So I mean, this is this is a buzzword, it is what it is, right? People hear of industrial IoT, or IIoT, which I can't say without stuttering a lot. So I don't want to say that a lot this episode, save our listeners from like, "Who is this idiot?" But anyway... So what's your take on this?

Amos  1:09 
Well, I would say because it's a buzzword, you should definitely be using it because it's easy way for money to get thrown at you. Yeah, and one of the best ways. I'm just doing this, I'm just doing IoT, don't worry about it. And I've seen people do that. But no, to kind of break it down, you know, Internet of Things. There's a lot of different definitions and stuff. But I think a really, you know, short definition is it's a device, small device, usually. But it can have some sensors have some capabilities, but you can easily disseminate them out. And they all connect up to a centralized system.

Now, how that changes to industrial IoT is obviously a little bit more of that industrial focus, usually a lot more specialized equipment. So it lasts longer, or it's, it's not just sensors out there. It's very specific sensors for a very specific reason. And really, the biggest benefit of IoT, just like IoT, IoT, you can tell if your bike got stolen, and the kid down the street has it. With like IIoT, you'll be able to tell if this machine has quality concerns, or this one part that just went by, you know, has a little bit of wobble in it. So you can really expand that out where your IIoT can be vibration monitoring and get you ahead of huge maintenance related issues. So IIoT, I would say the biggest thing is better data, more specialized data, more focused data, and being able to quickly deploy those very specific, for very specific purposes.

Chris  2:52 
Right, absolutely. I mean, data...It's all about data, right? I mean, everybody wants it. I mean, the watch I'm wearing now just gives you so much data and feedback. And basically to improve. from a personal standpoint, I need to move more and need to stand more all these things, the same type of technology is getting out into our plants. And like you said, they're telling us, "hey, I have a problem over here, come help me." You know, versus somebody actually have to physically say that. So it's really cool to see these types of devices and the expansion of IoT in the industrial environment. And one word I hear a lot of Amos, maybe maybe you can help it with. We're here, connectivity. It's another buzzword that's out there. Can you walk us through how that when you hear connectivity, how that changed the game regarding the plant floor?

Amos  3:38 
Yeah, honestly, mobile technologies have been great, but even just Wi Fi technologies, you're not having to run cables every time to go get data. That's an infrastructure-type connectivity that I think is just huge benefit. Getting a sensor up that can easily connect to Wi Fi, um, you know, you already have Wi Fi there, and all you have to do is go plug it in, versus Okay, well, you got to get the pipe fitters, you got to get, you know, an outside contractor to run the wires, make sure we have a port available on a server or a switch. That's huge, you know, that connectivity, being able to quickly deploy it, but even on top of timeframes, just the depth and the breadth of data you can get from these devices. You can get sub Second, you know, real time information. And it's not just what the graph plot on the side of the thing someone interpreted and came up and told you about it, you know, you've already got some aggregation of data in there. But IIoT gives you that just a huge amount of data that you really need to have to really do a lot of these more cool things, predictive maintenance, and AI and machine learning and that kind of stuff. You just need to have all of that data, be able to get it from all the different sources that can give you good data, and being able to connect to all those and quickly deploy those kind of things. So you Get a lot of correlation and really define and refine your process. It's huge.

Chris  5:05 
No doubt. I mean, you mentioned a few technologies there that I know have evolved through this, you know, the IoT onto the plant floor, such as remote monitoring, predictive maintenance, I mean, down to the way we're calculating OEE, right. So where do you see? And how are these items changing as this evolution continues?

Amos  5:25 
Yeah, everybody talks about predictive maintenance, definitely remote monitoring, I think that's biggest and first low hanging fruit type improvements that you can see that plant back out on the back 40, you know. But the predictive maintenance, you know, we can really start to see AI and machine learning, those are still pretty buzzwordy, but the technologies are getting there, where you will actually be able to use those, and you will use those in everyday life. And so, you know, with IIoT, the amount of data that they can get, the amount of good data that they can get, and have real time monitoring, really allows you to respond a lot quicker, and get ahead of a lot of problems. So you know, you're talking about predictive maintenance? Well, what if you didn't even have to predict maintenance? It just automatically triggered itself to go replace itself? You know, predictive maintenance could maybe be, you know, you never really have to worry about the plant going down, because it already knows how to go fix itself.

Chris  6:32 
Right? Absolutely. I mean, you've kind of touched on something here. There is so much data available now. And sometimes it can be very difficult to aggregate that and pull it together to make those decisions moving forward. What are you seeing as some common inefficiencies that plant operations may have, where if they could connect that data better make better decisions, could take them to the next level. Anything there?

Amos  6:57 
I don't know if you've ever seen the data pyramid? I also call it the wisdom hierarchy. So at the very bottom, we've got data. And once you create a whole bunch of data, you can get information from it, next layer up. And then from your information, you can gain some knowledge, you know, ways to improve your process and try some things out. But it isn't until you try some things out that you really get to the top of that pyramid, wisdom. And that's when you really start to make breakthroughs and improvements and that kind of stuff.

Well, at the very bottom of that is data. Sadly, most places, a lot of that data generation and gathering is done by people, when it could be done by IoT technologies, which not only is that Human Capital one that's repetitive, no offense, but humans are notoriously not that reliable. And about doing things repetitive every day, on time, that kind of thing, not near as reliable as IoT device. So that data generation by taking that off of people and putting something that you can get better results, more results. And having that good foundation of data, the people that were generating that data before gathering that data, considered that information, and that knowledge layer, you know, help better understand their process, not just go gather information about the process, no actually have all the information already there and focus on getting to meaningful insights instead of just getting it.

Chris  8:36 
Okay, so help me understand this. So basically, you're in this scenario, you potentially are elevating people, right, from the data gathering, to the information, knowledge transfer, or understanding of what the data is telling us. Is that correct?

Amos  8:50 
Yeah. And we talked about inefficiencies, honestly, every plant you go into, there's usually a process engineer that knows his process, down to a tee. And he knows everything that would need to be done, if we could get all the information to even start making that decision. So a lot of his, his time ends up being getting that information. And he can spot things ahead of time, right? He always knows, you know, the third press goes down. And this is what kind of precludes it. But he's constantly having to go check that one thing to make sure that it's all within its parameters. Well, the process engineer fee, if we were actually using him efficiently, then he could sit at "Oh, here's all my data. Oh, of course, that's gonna go down." You know, and he wouldn't have spent all that time trying to go and get it and he wouldn't have to spend time doing something that honestly someone else could do. His knowledge is more important being back there and being given the data.

Chris  9:53 
Right. In that though, Amos there was a big if there. If he can get the data. Which leads me to, you know, a question around communication, networks, processes. What needs to be in place so that he can get that data and they can move that information to make those decisions?

Amos  10:11  
Well, I think that can be a huge business shift for a lot of different companies, but to really embrace what IIoT really means, or even try to understand it, or try to use it, that can be a huge shift. But I think, obviously, you've got to look at your your business culture and what you're actually looking at doing with it. You're never going to get anything through if everybody thinks it's just the new kid on the block trying to do something. And yeah, well, those new technologies always fail, if that's the mentality, it's going to be really hard to start to deploy some of these.

But I feel like we're gonna have to. If nothing else, because the business cases justify it to get some of that data and start getting good information. But that all being said, definitely business culture, if you're already on board, how do you really go about this? I think security is something that a lot of times gets overlooked. And IT and OT, are notoriously not always happy working with each other. But that information that you're generating on the OT side, really needs to interact with a lot of the newer IT technologies and communication paths. And I think, you know, security is one of those ones that is only going to become more and more talked about and important. And so getting a good security plan in place and working with IT to kind of manage that, OT can use a lot of IP's communication paths and lean on them to establish good ways to start to get this information.

Chris  11:56  
Right, just businesses allowing the OT to spend that time gathering data, think more, make better decisions. All these things are so important. And so if I'm in a plant right now, and I want to make some of these changes, how do I know if I'm ready for this?

Amos  12:12 
Find a use case. There's so many different ways to justify an IIoT project, but doesn't have to be a major business shift. With the price point that you're looking at, minor process improvements, or even just better data that you really want to look into, maybe you want to do a deep study on quality on a certain part. Now, even just getting that one little IoT device that can go gather all that information, and you can get everything that you need, find that use case, and you can start down the road.

I would say unless you can get a lot of people, a lot of different departments in place to really dive into it and really want to start going after this. It's tough. And even if you get everybody's sign off, it's tough to do it right. You don't really need to go through that the learning lessons of what it means to deploy this kind of stuff, and set up the infrastructure to really start doing different things. Now, you know, setting up the infrastructure and doing a lot of the bigger picture, right, the end goal, you don't have to do right away. But you do have to have justification by the business to actually go after it.

So find little use cases, for one little thing, get a prototype out there, start getting the data. And I think that's one of the biggest things is really look at IoT, because because a lot of things, they do require a lot of data, or a long history of trends of good information to really start making your process better. So find the use case, start going after it. Start prototyping. Start doing small things. You might not get complete buy in, but you'll get a lot more buy in when you just save the company $100,000 a year.

Chris  14:03  
Right, kind of what I'm hearing too, and making the connection is you know, don't boil the ocean goes back to that old story. You know how to eat an elephant, one bite at a time. So start small, you know, find an area that you can make an impact. But it needs to be an area that you can make a measurable impact and from what I'm hearing you. Measure that, because then you can start building some cheerleaders around you and get that team and because usually once some of these technologies, you can see the impact. It's a lot easier to do Project 2, 3, 4 or 5. It's sometimes the hardest thing to get off the ground is project one because you got to prove yourself, right?

Amos  14:40 
It doesn't have to be the biggest project. Sometimes it's literally just seeing if a cold room is staying cold. And like it can be something small, but uh, you hit on a good point. You know, how do you know if you're IoT ready? If you've got cheerleaders already in there and they've already done it and they're excited about it. They know what it can do. You have people throughout your organization that are ready to start going after it, you know that you'll be able to find a use case.

Chris  15:09 
Exactly. I mean, this has been great Amos. I mean, this has really been a good breakdown of industrial IoT for our listeners. And we love the wrap that the EECO Ask Why with the why. I'm anxious to hear your take on this because you have such an experience in manufacturing. You're out with end users all the time. If somebody was to sit you down in a room and say, give me the purpose, talk to me about why this is important. So why would be embracing the industrial IoT be important for the future of manufacturing?

Amos  15:39 
Efficiency. We look at a lot of our plants and our processes. And we try to make them more efficient. We probably have already got all of our low hanging fruit. And we already figured out how, which data we needed to gather to go after what we knew about. But you don't know what you don't know, until you start getting better data and more data. And you can start elevating it to people where they start making decisions and already have the data to start making those decisions. And only then will we really start to unlock the true impact in our efficiency in manufacturing.

Chris  16:17 
No doubt it's exciting to see where it's going in the future, isn't it my friend?

Amos  16:21 
Yeah, it was pretty fun to be in it.

Chris  16:23 
That's what we're trying to inspire people to come to it. So I mean, Amos this has been wonderful. Good overview of industrial IoT. A fundamental discussion here, but I think we went pretty deep in some areas, and hopefully connected some dots for some listeners. So man, thank you so much for taking the time and the knowledge and insight that you provided today.

Amos  16:42 
Yeah, thank you guys for having me.

Chris  16:44  
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