John Clemons, director of manufacturing IT at system integrator Maverick Technologies, a Rockwell Automation company, talks with Jim Montague, Control’s executive editor, about recent developments with the Industrial Internet of Things (IIoT), how it's enabled by edge and cloud computing, and potential users can employ it for digital transformation, especially in light of the recent COVID-19 crisis.
Transcript
Jim Montague: Hi, this is Jim Montague, executive editor of Control magazine and controlglobal.com, and this is the latest in our Control Amplified podcast series. In these recordings, we talk with expert sources about process control and automation topics, and try to get beyond our print and online coverage to explore some of the underlying issues impacting users, system integrators, suppliers, and other people in organizations in these industries.
For our latest podcast, we're talking to John Clements, director of manufacturing IT at system integrator Maverick Technologies, www.mavtechglobal.com, and Maverick is also a Rockwell Automation company.
And we're talking with John about recent developments with the industrial internet of things, how it's been enabled by edge and cloud computing, and how potential users can employ it for digital transformation, especially in light of the recent COVID-19 crisis. All right, well, John, sorry for the usual lengthy preamble, and thanks for joining us today.
John Clements: Hello, Jim. Thanks for having me on. Good to be here. I appreciate the opportunity.
Jim: Okay. When we talked for Control's February cover article on edge computing, I think you stressed that using the word edge was kind of a misnomer because the focus should be on what needs to be done with all the data coming in for process applications rather than where it happens on the network. So, if so, you know, how should users think about how to handle their data?
John: Well, Jim, I think the reason a lot of people call it edge is because it's edge in reference to the cloud. So, it's kind of like on the edge of the cloud before you get to the cloud is kind of the idea behind that name. But if you actually think about the data and where the data originates from, one of the things we're seeing with Industry 4.0 and smart manufacturing is a proliferation of smart devices on the shop floor.
So, all kinds of smart machines, smart devices, smart applications, everything with all this proliferation of applications and smart machines as far as devices is a proliferation of data. So, if we've got all this data on the shop floor, what are we going to do with it?
Well, some of it is going to need to go to the cloud, and there's lots of good reasons why it can and should go to the cloud. But there's also no reason why a lot of the data can't and should stay right there on the shop floor, because the people on the shop floor are the ones that are going to be using it to do what they need to do with their jobs. And that includes things like dashboards, analytics, maybe even advanced analytics, and even AI kind of applications.
So it doesn't make a whole lot of sense to send up a lot of data to the cloud only to bring that data right back from the cloud to use it in AI applications around machine or equipment performance. So, the idea is to use edge computing right on the shop floor as part of the edge solution, and that data can be then used in analytics and machine learning applications in AI applications so that the end result is we get the data back to the people that need it on the shop floor as quick as they can. And that data is useful to them without making some big, round trip circuit up to the cloud and back.
Jim: Right. So, how can that approach help when considering how to use the, you know, the industrial internet of things, devices, and software cloud computing services or other forms of digitalization?
John: Yeah. So, one of the things that we're seeing around the industrial internet of things is this big proliferation of these smart devices and smart machines, and things like that and all of the data.
The industrial internet of things has become an almost ubiquitous background foundation kind of backbone for managing all of this equipment, all of these smart devices, and all of this data to the point now where IIoT solutions are pretty much required in any kind of factory shop floor setting. Because there's just so many smart devices now that you have to have something like the IIoT out there to manage that and collect the data, and do something useful to keep it all straight.
So, then with that as a backbone, you need to think about what data is needed where, what applications are used where, and then that can lead you to the right architecture around edge computing and cloud computing. So that I get the right data it has to go in the cloud. And there's lots of good reasons for that because people are going to use it all the way across the organization, and you're going to use data into the cloud to supply data to your suppliers to give data to your customers, because that's part of the business and the globalization world that we live in today.
But when you've got data that's needed on the shop floor by the people running the equipment, you can just put it in edge devices and let them do it, do with it what they need to right there, and then the edge devices can provide the data to the cloud.
And so, you end up with a best of both worlds having edge computing and cloud computing. So you're not only getting the right data to the people on the shop floor but you're also getting the right data to everybody in the enterprise and even in your extended enterprise to both your suppliers and your customers.
Jim: Right. So, it's just kind of a side question that's part of the evaluation process at the beginning is to decide, can we do the basic calculations and then report up to higher-level, you know, functions and analytics as needed? This used to be called, like, report by exception, right?
John: Yup. That's correct.
Jim: Yeah. Okay. All right. So, then the follow up would be, you know, how have yourself, and Maverick, and your colleagues applied IIoT tools and digitalization principles on some of the projects that maybe you've been working on?
John: Yeah. So, one thing that we've seen that I think has kind of been a little interesting, maybe even a little funny if you think about it, in the last couple of years, people have been, in some cases, maybe a little reluctant, "I'm not sure I really need to do all that, this edge computing, this IIoT platform, all this kind of stuff." And we'll kind of encourage them to do that as a particular pilot, you know, as a proof of concept.
And they'll do that and it'll be wildly successful, and then it'll be completely kind of maxed out, their little pilot, to the point where, "Hey, we need to do this in the whole plant." And it's, like, "Yeah, yeah," but they kind of have to see it to actually see what it can do so they kind of believe it.
So, the pilot is a great approach to do this kind of thing, but we're seeing very quickly that people that do pilots around IIoT platforms, around edge and cloud types of solutions that the very quickly they see the benefits of that, and then very quickly scale up to maybe the entire plant and eventually to the entire organization.
So, one of the things that we've found is very, very important when we're putting in these kinds of solutions, even on pilots as small as a single line, is that they have to be scalable. And they have to be scalable very quickly because the clients, our customers, are not wanting to do a pilot and then find out that they've got to do some kind of major project to scale that up.
They want a very simple and easy method to scale that. They want to be able to scale quickly, and because it not only scale in terms of, say, number of users, number of machines they connect up, but once they start getting these kind of platforms in place, they start kind of discovering pockets of data. They find machines, devices that have more data than they ever thought that they had and they're finding users for that data.
And so, it scales very quickly in terms of number of users, number of devices, but also scales very quickly in terms of just the amount of data and the data throughput. So, that's something that we, as Maverick, are required to kind of think about when we're working with our customers to make sure we do that engineering work upfront so that these kinds of things are taken into account so they can scale very quickly. And so, that's just a couple of principles that we kind of had to adopt when we're doing these kinds of projects.
Jim: Right. So, then what were maybe some of the unexpected obstacles or pleasant surprises that, you know, you and your clients encountered as projects like this progress?
John: Well, I will tell you this is that some people often think of some of this kind of technology as sort of a silver bullet, you know, "Hey, this technology is going to solve a lot of our problems." Well, it's definitely going tosolve a lot of problems because it does a lot of really cool things, that's for sure. But problems that are based on the way your business is operating, the way your culture has been set up, the way that your processes work is where a lot of the obstacles come in.
So, it's a lot more than just the technology and implementing some good technology, whether it be edge, or cloud, or IIoT, or other smart manufacturing Industry 4.0 kind of technologies. It tends to be more about the people, about the culture, and about the business processes.
So, if you don't have the people and the teams kind of together, you don't have your operating strategies, your manufacturing strategies together, you don't have the right kind of culture for change and the right kind of approach to doing this Industry 4.0 kind of thing, then even the best technology in the world may not do a whole lot for you.
Because in the end, smart manufacturing is really not only about smart technology and smart devices, but it's really about smart people using those tools because they are just that, tools in the end. And so, that's why business strategy, teams, people, cultures, and business processes are so critical to the success above and beyond just the technology.
Jim: Right. Well, I presume that the folks, like you said, who've done the pilot, they've maxed it out and because they've done that they're convinced that the new technology would be useful. You know, are there ways they can go about convincing maybe more reluctant managers and leaders to help them scale up?
John: Yeah. So, there's several things there. You know, number one is as much as people might not want to say it this way, but it's kind of, like, it's sort of a sales activity. It's, like, never stopped selling. You've got to be an evangelist. You got to be looking at what it's doing, which means ultimately, you've got to focus on the business case.
I mean, bottom line, the technology's cool, okay, smart manufacturing Industry, 4.0, it's all really great stuff, but it's really all about the business case. And so, focusing very heavily on the business case is always the right thing to do, and being able to go back and focus on the actual benefits that are being achieved. So when we're doing that kind of pilot, one of the things that we want to get involved in a pilot project from the very beginning is the finance people.
The reason we want finance people involved isn't because they're the ones that have to pay for it, but that they're the ones that have to show the benefits that we're actually showing benefits on the bottom line. Whether it's, like, the controller of the plant or whoever it needs to be, we want those people as part of the project from the beginning to define exactly the metrics that we're going touse, and that's metrics that have dollar signs in front of them, those metrics that we're going to impact with this project.
And we want to be able to track that impact on a month-by-month basis. So, when we put that pilot in and we go from month to month, we want to be able to see those impacts, and we want to see those dollar numbers changing in that plant so that we're actually having the impact that we say we're going to have.
Jim: With part of the evangelizing that goes on, does it include letting people know that maybe a lot of the IIoT tools are a lot easier to connect up and configure. And, you know, unlike the traditional PLCs and DCSs, you know, many of the IIoT-type tools are easier to plug in and configure and get up and running than maybe people would otherwise think.
You know, traditional engineers might think, "Oh, man, I'm going to have to do a lot of typing in code," whereas connecting these things up, it's much more easy to connect them and just, you know, click off a couple of boxes and you're off and running as opposed to typing in code. Is that fair to say?
John: Yes, that's fair to say. Most of this technology is actually very easy to use, it's very simple to use, but, you know, people still resist change that there's always the fear of the unknown. And for people that work at these facilities, there's always the fear of losing their job. Because anytime anybody wants to bring in new technology that does anything new, it's always, like, "Well, you're trying to do that in order to push these people out of their jobs."
And actually, in most cases that's very far from the truth because most of those kinds of changes in the manufacturing processes were done decades ago. Okay? And then what we're trying to do with these kinds of Industry 4.0 tools, whatever kind of technologies they are, we're just giving them, giving the people more tools and more abilities, and more capabilities to do things they couldn't do before.
So, I was, again, trying to emphasize, it's about smart technology, sure, but it's really about smart people using that smart technology. And ultimately, it's the people that have to be able to do what they need to do to achieve the benefits in the business, leaving the technology to do what it does best but then leave the people to do what they need to do best.
So, focusing on the people, focusing on giving them tools, making the people better at what they do, highly skilled, highly trained, you know, veritable experts in being able to do this is the idea behind giving them these kinds of tools.
Jim: Yeah. Well, are there any other lessons learned or advice that you might have for our listeners about implementing, you know, IIoT in their applications and facilities?
John: Yeah, sure. And I think that, you know, again, my number one advice would probably be to think about kind of the big picture of what you're doing. These tools come and go, but ultimately, it's about your strategy, it's about your people, it's about how your teams are working, it's about your culture, that those are the fundamental things that are going to really make or break the success of a particular project.
And, you know, the cool technology you're using today might not be what you're using a couple of years from now. I mean, the technology landscape is changing very rapidly. So, you don't need to think about, "Well, we're going to be picking something that we're going to live with for the next 20 years or whatever," and then you spend months or years trying to pick something or whatever. That's not the way it works anymore.
There's a lot of tools, they change. It's, like, pick something, go with it, get it doing what it needs to do, but think about the culture, the environment. There's going to be lots of tools that are out there. But if you've got the right culture, if you've got the right people, the right teams, the right kind of strategy put together, you can be successful with any kind of tools, then you can pick tools, you know, however you need to.
You find the right tools that they need, and today they might need this particular tool, next year they might need something different, and the year after that, they need something different. But that's all good because you're giving them what they need to do to be successful, and they're going to be successful with it if you focused again on the strategy, the teams, the people, the culture, and not so much the technology.
Jim: Well, the process industries had to, you know, put in equipment then early software that had to be the same for 20, 30, or more years. And then folks kind of were unhappy with having to change software every few months. But I guess the silver lining is that now the IIoT tools can be updated and, you know, switched over at pretty low cost, and it's easy to do. So, it really requires that shifted mindset from stuff that's going to be in place for 30 years to...
John: Yep. That's true. And you can think about that in the same way you think about your smartphone. You know, I mean, what is it, everybody gets a new smartphone now about every year, every other year, and you get, you know, just download new apps on your smartphone, you know, anytime you need them. And if this app, you know, is what you're using today, it's probably not the app you might use six months from now.
So, it's the same kind of thing. It's just a tool, and we're going to use it to do what works right now. And the other thing that I think is so critical about this technology, why it makes it so successful, is there's so much of it, so plug and play. You were talking, Jim, about, you know, how quickly you can get some IIoT things set up, particularly compared to, say, DCS or PLC kind of systems from, you know, years past that required a lot of programming and a lot of logic, that kind of stuff.
You know, the new applications, whether it be IIoT, you know, edge, cloud, whatever it is can get implemented pretty quickly. They're a lot simpler, they're easier, they're very plug and play. And that's the benefit of IIoT platforms is that you can just plug and play in applications, plug and play devices. We're even working on new things that we're calling smart objects.
So, the idea behind smart objects is actually to have what also might be called, like, intelligent agents that are part of an IIoT platform that actually is smart enough to actually navigate through the platform and go from device to device kind of checking on things and actually kind of working, if you will, as an agent to facilitate transactions between the devices, but also to facilitate data, and to do data collection and other things.
So, when some type of anomaly is detected at one particular device, then the intelligent agent or the smart object might then start looking upstream and downstream for similar anomalies as whatever the event or whatever's happened starts to spread from there and impact upstream and downstream operations.
And so, as these kinds of intelligent objects are smart objects, intelligent agents, that can navigate through this IIoT platform. And all of those are just kind of plug and play but then work as facilitators. And, you know, we're not maybe quite there yet with all of that, but that's where we're going and that's going to be another wave of stuff that we're going to see.
Jim: Right. Are these objects and agents, would they be at all similar to the function block software, the reusable function blocks that people might have encountered in the past, or are they enhanced?
John: That's actually a good point because they've actually grown out of that kind of concept. So, you can kind of think of that kind of concept as the small infant of the idea, and it's now grown many, many generations past that to now these smart objects and these intelligent agents and several things. But that's very, very intuitive there because that's exactly the ultimate foundation of where this all started many years ago.
Jim: Yeah. Just as a final question, our recent events, you know, such as the, you know, COVID-19 crisis, are they accelerating adoption of IIoT, edge, cloud, virtualization, and digitalization in general? And if so, how should implementation maybe be altered or adapted?
John: Well, I think the COVID-19 crisis is obviously affecting everything we do. And one of the things that is affected negatively is, obviously, you know, travel. And without the ability to visit some of these plants it's kind of difficult to actually, you know, get your feet on the ground and see what's exactly going on. But in general, throughout the industry, we're actually seeing things accelerate, because people are starting to get serious about this stuff.
They're finding ways they need to do this. They're realizing that they can't just go see what's going on. They need to be able to do things remote, and they're bringing in teams of people and bringing in people throughout their organizations from different locations. And they're realizing now more than ever that having the right data at the right people throughout their organization, throughout the world is very important. So, I think that's definitely accelerating the idea of IIoT in general, about cloud, virtualization, digitalization, that all of that is definitely growing.
Also, we're seeing things like digital twin and digital thread being expanded as well for the same reasons and just other aspects of all-around digitalization and just the digital transformation I think is being accelerated at this particular time, not only because of the particular crisis, but I think just a lot of things are coming together.
And it's kind of, like, you know, if now is not the time, then when? And I think most people are answering that to say, "Yeah, you're right. Now is the time. We're going to get serious about it. We need to get serious about it now." And that's what we're seeing.
Jim: Cool. All right. Listen. Well, John, those were some enlightening insights, and thanks for speaking with us today.
John: Oh, it was my pleasure. Thanks for the opportunity. Thanks for having me on. I appreciate it, Jim.
Jim: All right. Well, this has been another Control Amplified podcast. I'm Jim Montague. Thanks for listening. And please remember the Control Amplified podcasts are available on most podcasting apps, such as the iTunes Store, and Google Play, and on Control Magazine's YouTube channel podcasts, plus you can always just go to controlglobal.com and listen to them right away.
For more, tune into Control Amplified: The Process Automation Podcast
