Solving Data Problems to Accelerate Digital Transformation

59 min video  /  50 minute read Download PDF View slides


Arlen Nipper

President & CTO

Cirrus Link Solutions

Kevin McClusky

Co-Director of Sales Engineering

Inductive Automation

Eric Hollering

Software Architect

Flexware Innovation

One of the biggest Digital Transformation challenges companies face is how to make the most of their data. Problems like stranded data, lengthy setup times for systems, and difficulties bringing IT and OT data together inhibit an organization’s ability to gather insights. Without these insights to fuel the decision-making process, many companies end up stalled on their Digital Transformation journey.

In this webinar, we’ll explore common data challenges and the features in Ignition that empower industrial organizations to overcome them. Join us to learn how to remove the roadblocks to innovation and enable rapid progress in your Digital Transformation.

  • See Digital Transformation success stories
  • Solve challenges in collecting, modeling, and accessing data
  • Put data to use in business and industrial applications
  • Leverage analytics and machine learning tools for valuable insights

Webinar Transcript

Kevin McClusky: Hello, everyone, and welcome to The Inductive Automation monthly webinar. This one is the month of June 2022, and I'm excited to be talking to you today about Solving Data Problems To Accelerate Digital Transformation. We're so glad that you're here. I'm gonna be talking to you about this and then other folks are as well, so we have a good set of speakers here, and these folks are industry veterans, and you may have heard from Arlen before in the past. Eric is someone that I haven't worked with before but has a great amount of background and history and some really good insights to share with all of us here today. My name is Kevin McClusky. I'm Co-Director of Sales Engineering at Inductive Automation, and I've been with the company a little over a decade. So it's been an interesting journey. I go pretty deep on the technical side but I also get very excited about business outcomes and different steps in the journey of Digital Transformation that our customers are going through, and I work with hundreds of customers on their Digital Transformation journeys here. So I'm happy to be here. Arlen, Eric, maybe you can go ahead and introduce yourselves and take just a minute to let folks know who you are. So, Arlen. Starting with you.

Arlen Nipper: Thanks, Kevin. So, hello everybody. My name's Arlen Nipper. I'm the CTO for Cirrus Link Solutions, and I've been doing industrial from all the way from working for oil and gas companies to designing better computers to network and architecture infrastructure for 43 years now. Halfway through that career path, I was very fortunate to be able to work with Andy Stanford-Clark from IBM and was one of the co-inventors of MQTT. So, very interested in this webinar and how we're going to use technologies like MQTT and the tools in Ignition to solve these problems.

Kevin: Thanks, Arlen. Eric, over to you.

Eric Hollering: Hi. I'm Eric Hollering. I am a Software Architect with almost 20 years of experience writing and managing software in the manufacturing industry. I've been with Flexware Innovation for the past five years of that journey. I've used many languages and tech stacks, but mostly C# and other tools in the Microsoft ecosystem over that time. About a year after joining Flexware, I saw a demo of an integration project for autonomous mobile robots that was done by a co-worker in Ignition, and got excited about that and got me involved in the next project, and thus involved with Ignition over the past several years.

Kevin: Great. Thank you, Eric. And once again, thanks, Eric, Arlen, for joining us and sharing your insights and knowledge with the audience here. We really appreciate it, and I'm sure that they do as well. And so I'm gonna go ahead and hop right in to talk a little bit about the agenda. So the agenda for the webinar, in case you're not familiar with it already, I'll start off and quickly tell you about our software platform called Ignition, and then we'll cut through the mystery, and we'll try to clarify what Digital Transformation is really about. Then we're going to talk about some of the most common data problems that stand in the way of Digital Transformation and how they can be solved, which will lead us into talking a little bit more about Ignition as a platform for Digital Transformation . After that we'll share some success stories, go over the benefits of Ignition, and we'll wrap up with some audience Q and A. If you have questions, this is an important note here, type them into the questions area of the GoToWebinar... The GoToWebinar, sorry, control panel, and we'll answer as many questions as we can at the end of the webinar. So we'll hold answering the questions for the most part until the end, but go ahead and familiarize yourself if you're not already with where that questions panel is, and feel free to enter those questions as we go along as they come up, and we'll throw those to the right folks when we get to the Q and A section at the end.

Kevin: So a quick introduction for those who haven't heard of Ignition already, Ignition is known as a great HMI and SCADA software solution, but it's actually an unlimited platform that can do a whole lot more than that. Ignition lets you connect, design, and deploy without limits, it provides one central hub for everything on the plant floor, it lets you easily create any kind of industrial application, including IIoT and MES solutions, and a whole lot more in terms of the types of applications that can be built. Folks are building things from everything from nuclear radiation detection systems, to standard manufacturing systems, to airport baggage handling, claim systems, to just about anything you can think of. You can instantly web deploy clients to desktops, industrial displays, and mobile devices. Ignition's unlimited licensing provides all of the client's tags and connections you need at one affordable price, and it has industrial strength, security and stability that today's world really demands. All of this is why Ignition is trusted by 57% of the Fortune 100 companies and thousands of other companies worldwide as well. Alright, now that we've introduced Ignition, let's jump over to one of our main topics, which is Digital Transformation.

Kevin: Many of you probably noticed that our company is talking about Digital Transformation a lot recently. It's not a brand new concept, most companies are already aware of Digital Transformation and have been for years as they've tended to view it as a long-term goal to gradually work toward, but now it's really been picking up more momentum.

Kevin: A lot of folks may not have recognized the urgent need for Digital Transformation before the COVID pandemic, but they're certainly seeing it now. That's why there's a large-scale velocity of companies accelerating their Digital Transformation journey and Inductive Automation is a major catalyst in this movement. But before we talk about why Ignition's ideal for accelerating Digital Transformation , let's quickly clarify what Digital Transformation really is about. So we're going to understand what we should be accelerating toward. Digital Transformation obviously has a lot to do with technology, but it's not about technology for technology's sake or just putting new technologies on top of old ones, rather it's really more of a comprehensive shift in the way that we do business. It's all about finding where there's room to improve our operations, then making those improvements in an intentional, methodical, and measurable way, leveraging modern technologies like cloud, Big Data, edge, and IIoT. Therefore, we should really think about Digital Transformation in terms of the different components and we at Inductive Automation have split it up into three different sections. We've worked with a lot of companies and found that there are some consistencies in terms of what different areas people need to focus on.

Kevin: So if you slice and dice that, you can break it down into processes, people, and programs. In terms of processes, we should really look at existing processes and ask, how can we streamline them? How can we rethink them using digital technologies? Can we create new processes where necessary? How do we overcome entrenched ways of doing things? If you think about people, think about the people inside the organization, how do we increase communication and collaboration? Could we improve our decision-making by making data more widely available? How will we teach our people new skills? How can technology help us improve the user experience? If you think about processes, processes are basically how a business is running, people are the ones who are making decisions as to which processes to actually employ, how to employ those processes and making decisions where processes don't exist. And then the last piece right here is programs and should really review those programs or our technology. And people, process, programs is three P’s. It's easy to remember that programs could also be labeled technology there. So we should really review those programs and think about the following: How can we improve operational efficiency and increase savings, how do we remove the limits imposed by outdated technology, and how will we navigate compatibility issues and avoid disruption or downtime?

Kevin: All three of these pieces are very important. We'll be focusing for most of the rest of the webinar on the program section or the technology, but make sure you don't lose sight of processes and people. Effective Digital Transformation really requires all three of those parts. And so let me talk a little bit about something that's more abstract here. So I have a young daughter, and if I wanted to build her a playhouse, there would be a few steps. I can get the wood, have it shipped, put it in the backyard and have it ready to go, but if I didn't have any tools, it would be really impossible to build it, at least using modern efficient construction techniques. I'd be sitting in the back with a bunch of cut pieces of wood, not knowing what to do or how to put them together, if I didn't have any nails, if I didn't have a hammer. You need tools in order to do things in modern ways. And it's interesting, I have a staple gun that was passed down to me by my father. It worked great, but as soon as I ran out of staples, I went to the store to try to get more staples and well... You guess where this is going. They didn't have any staples that were the right size. There is a special staple size that isn't the standard and it isn't available, and for me, it made the tool practically useless going forward.

Kevin: This problem that I'm describing exists in the software industry as well. Proprietary tools that don't use standards can make life difficult for everyone. And I really like this analogy because I think that it brings it home, why having standards, why having standard technologies and why having standard sets of programs and the technology behind them is really important and brings it home in a way that is relatable for anyone who's ever tried to build something. So, Eric, I had wanted to ask you a question, throw this over your way, as an integrator, do you have any comments about the importance of having the right digital tools for Digital Transformation?

Eric: Yeah, absolutely. Using standard tools within a tool set is essential, and strictly what I'm looking for in a tool set is depth extensibility, integration capabilities, protocols, and things like that, that are just standard that you can use out of the box to integrate with other things, because nobody wants a solution that exists in a silo. What I find is that depth usually comes with the cost of accessibility, which is why I've spent a lot of time in C#, but Ignition does a great job of meeting people where they're at to get them off the ground running quickly and still enabling them to go deeper and dive deeper and build cooler things as they progress in the stack. So that's kind of what I liked about it.

Kevin: Thanks, Eric. Arlen, did you have anything you wanted to add to that?

Arlen: Well, yeah. I think when we talk about Digital Transformation , there's this propensity that, "Oh, it's Digital Transformation , therefore we must go write code," and we're all about... And part of this webinar is about tools on platforms, not coding on operating systems. So I think the more that we can use the tools that Ignition as a platform... Forget about whether it's SCADA or HMI or DCS or whatever, it's really about the tools on a platform that we're gonna leverage.

Kevin: Thanks, Arlen. Yeah, it's interesting to me, too, that... Eric, you mentioned C# in there, and I've definitely programmed my fair share of things in C#. I come from a very technical background, and the difference between building something using tools versus building something using code, using basically going really low level as opposed to using tools to build something in a more rapid way is something that originally drew me to Inductive Automation. That's something that made me wanna work for Inductive Automation, have a hand inside Ignition. So you're speaking... You're a man after my own heart there, Eric. So thanks, guys.

Kevin: The next item that I want to talk about here is a little bit more about really another big Digital Transformation challenge. But one of the things that companies struggle with is how does that make the most of their data? And fortunately, we're able to help with that, and part of that is... Well, actually, don't take it from me, we have someone who's a very deep expert when it comes to these challenges with data inside the Digital Transformation space, and I'll hand that over at this point. So Arlen, can I tag you in to talk a little bit about this whole Digital Transformation data space.

Arlen: Thanks, Kevin. Will do that. So I really don't know why we're talking about this, Kevin, because we all know that Modbus has been around for the last 45 years, so we're probably good to go, right? So... But you're right, data's vital to decision-making and in many industrial organizations. Huge amounts of data are stranded in data silos and inaccessible. I would say that... The proponents will say 80% or more of their important data is stranded in their field devices, and I will argue that in many industries, that's probably closer to 90% to 95% of information that we could be using is stranded either in the devices or in the applications that are polling the devices. So when we look at this and we think about... Well, we really... Our mantra has been for Digital Transformation is number one, whenever possible, connect devices to infrastructure, not to applications. Number two is to be able to provide a single source of truth for your process variables and for your models as far out in the edge as you can, and number three is — be able to show, demonstrate, a better, faster, more reliable, more scalable, more secure OT system, first and foremost. Because if we can't do that, we won't get the tools in the field that we need for real Digital Transformation.

Arlen: So when we couple devices, kind of hard code them, if you will, with a protocol to another application, we can't be serendipitous with that data, and the other thing is that taking again, my example, Modbus, so I've got Modbus register 40001. It's got a value of 12, right? That's all I know. Well, I have to add, as a human, I've gotta go in and edit that point and give it a context. I have to give it a name, I have to give it a value, I have to give it an engineering high, engineering low and any other thing that I want to associate with that process variable.

Arlen: So if we look at the proposition today versus the reality, is that up until now, what we've been looking at is, again, there's this propensity to... Oh, it's Digital Transformation , therefore it must be IT down to OT and don't get me wrong, the tools and the capabilities that we've got with cloud computing are awesome, but we've got to think of it the other way around. Think of it as, the reality is we need to get the tools and the platforms in place to enable our OT infrastructure to be cloud ready to start with. So this isn't IT down to OT, it's OT tools in the plant, in the facility, giving us the capability to be ready to plug in the cloud applications as they become viable. So what we're talking about here is kind of a data problem, if you will, of OT data, which again, this is tribal knowledge and the fact of the matter, is that for the next decade or probably even more, we're gonna have to deal with the fact that we've got proprietary data, we've got processes, we've got tribal knowledge on the plant floor, and we need the tools to be able to take that data, give it context so that we can start meeting the needs of IT.

Arlen: Now, I look at this, and we say, "Oh, well, come on, guys. That's a value of three." And we are guilty, if you will, as OT, as PLC programmers, as technicians of not understanding that our data, although we may understand it on a day-to-day basis, we're not making it very friendly for other people, other applications within the enterprise to discover that data and to be able to make it available to everybody in the enterprise. So Ignition solves this problem by giving us a set of tools to seamlessly bring OT technology and IT technology together in an open platform based on IT standards. So Ignition talks to PLC just as easily as it talks to an SQL database, which makes it easy to get access to all of your enterprise's important data on a single platform. So to talk more about how admission can empower Digital Transformation . I'm gonna hand it back over to Kevin.

Kevin: Thanks, Arlen. So Ignition really helps companies solve their data problems by making data easily accessible to anyone, this democratization of data really helps companies digitally transform their processes to be more efficient. If you look at this graphic that we put together, we're really looking at the whole picture and taking a look at the whole picture, it's important to understand the parts that go into the whole and what your organization really needs to transform each item here from a traditional model to modern set of technologies and capabilities is going to be potentially similar and potentially different for each one of these steps. So just reviewing this at a high level, the first is collection. Collection is where data is collected from devices or other sources on the platform or the field. Data modeling is where data is structured in a unified way and it's made easy to understand. Publication and subscription... Well, really, data needs to be accessible in an open, secure format, supported by industry standards and strong security for industrial and business applications. That fourth item right there, after data is accessible, an organization needs to be able to see and explore data. Data is turned into insights and action through the creation and connection of industrial and business applications.

Kevin: The last item there, analytics and machine learning, really, no system today is complete without insights that are, honestly, very valuable, that can be garnered through analytics and machine learning tools. So let's explore how Ignition addresses each one of these areas. If we start with data collection, this is a challenge for many companies today. To solve this challenge, Ignition leverages open standards and modern technology to act as a hub for everything on the plant floor. It can connect to virtually any kind of PLC through native drivers or through OPC. It supports all major databases, historians, other ERP, and MES systems, any third-party web service, RESTful communication, SOAP-based web services, integration with cloud services like Azure and AWS, and the ability to get data to anyone on any device.

Kevin: By leveraging MQTT, Ignition provides a streamlined data pipeline for IIoT, which we'll talk a little bit more about in a second. And as you can see, really, Ignition bridges that gap between the OT and the IT data on that data collection and connection side and enables that total system integration. Of course, after collecting the data, it's important to go to the next step, it needs to be modeled. A few devices and edge systems support proper data modeling, but most do not. Whether they do or whether they don't, Ignition either enables using existing models or it allows folks to define your own models. Once again, I'm going to bring Arlen back. Arlen's an expert on data modeling and the Sparkplug specification. So I'm gonna give you the mic for this part, too, Arlen.

Arlen: Thanks, Kevin. Appreciate it. So Sparkplug, it basically provides a standard for modeling OT data. So it's a specification that defines how to use MQTT in a mission-critical real-time environment. It's important to understand Sparkplug does not change the underlying MQTT transport in any way. One of my favorite sayings is that the great thing about MQTT is you can publish anything you want on any topic. The problem with MQTT is you can publish anything you want on any topic. So really, at a high level, what does Sparkplug do? Well, the first thing it does is it defines an OT-centric topic namespace. Now, what this results in is plug-and-play auto-discovery. If you know just a little bit about pub/sub systems is that you've gotta be able to go in and basically do a wildcard subscription on a given topic so you can discover things automatically. By having the notion in Sparkplug of a group, a node, and a device ID, we immediately know that a new device or a new sensor has been added and what it can do for us. So in other words, the sensor is telling us about itself, so plug and play.

Arlen: The second thing MQTT Sparkplug does is it defines an OT-centric data model and asset structure. Now, this is... It's very important. It's kind of an epiphany that we've had over the last four or five years working with customers, because originally, we were really focused on having the single source of truth for a measurement, for a process variable, for an Ignition tag, to be able to define that tag, to give it a name, to give it a value. But what we were finding as we start migrating into other applications, especially in the cloud, we need to be able to define that model all the way at the edge. So imagine with an Ignition system, being able to take and build a model with your tools, i.e., building a UDT, we can publish that model directly from the edge of the network.

Arlen: The third thing that Sparkplug does is it defines an OT-centric process variable payload. So again, I'll go back to my Modbus example, where for the last 40 years or more, we've been stitching together Modbus register value pairs. We had to manually go in, give it context. With Sparkplug, at the very edge, we can use the Ignition tools to give that measurement a name, a value, a timestamp, a data type, engineering units, engineering ranges, quality and any other custom property we wanna add to that measurement to give it context for everybody else in the enterprise to consume that. Again, give it context so that not only the engineer, the program, the PLC knows what the heck that value is.

Arlen: And then the last thing that Sparkplug does is that... As we've defined or described before, is that MQTT lets us do report-by-exception. In many cases, that looks... You're looking at reducing the overall bandwidth required for the same number of process variable updates, 80% to 95% less bandwidth to do that over your network. But to do that, you have to have proper state management. So Sparkplug defines that death certificate, if you will, of MQTT, and then that lets you do some pretty cool things, including store-and-forward. It's interesting that five years ago when we started working with Inductive Automation, there was this notion of, "Hey, if my network goes down, I'm gonna have holes in my time series database." And now, probably 95% of our customers use the store-and-forward capabilities of Sparkplug so that even if the network goes down, those process variables that would have been published are put into a queue, and when our MQTT session comes back up, those are slowly fed into the Ignition historian. So basically, Sparkplug gives us that single source of truth.

Arlen: Now, when we look at using Ignition for Digital Transformation , it simplifies access to data, and it's important to have this architecture that can scale and doesn't require a one-to-one link from devices in the field to applications. MQTT's overall Pub/Sub model is the ideal data, ideal solution, for decoupling your OT data from the enterprise. So if we look at that using Sparkplug, Ignition can leverage the efficiency of MQTT to decouple devices from application, creating one streamlined data pipeline. MQTT has emerged as one of the leading protocols for IIoT, and ironically, although I'd say MQTT, it was invented for SCADA and adopted by IIoT, but we're now getting MQTT back into applications that it was originally designed for in the oil and gas industry for over 20 years ago. Ignition's IIoT solutions leverage MQTT to easily publish data from thousands of plant floor or field devices to a central location where both industrial and business applications can subscribe to that data. Because MQTT has that pub/sub model, you just subscribe to data that you want.

Arlen: Now, if we start looking at that concept that I told you before of data models, well, now we're starting to realize that initially, we were taking measurements and we were pushing them into data lakes or S3 buckets, and we kind of realized that we de-materialized all of that knowledge that we had at the edge. We broke it up into all the individual measurements, and then we push it all up into a data lake where we've gotta hire somebody to put it all back together again, where what if we could just take the models that we built in Ignition and immediately have them show up?

Arlen: So Azure is offering their Azure Digital Twins service, and then what we've worked with a lot here lately is with a new service from AWS called SiteWise. Now, SiteWise is a cloud service that at its roots, you have to define a model. And once you've defined a model, you instantiate that creating an asset, and then the asset has measurements that go into the time series database on the AWS SiteWise service. So what we've done is that being able to use that with MQTT Sparkplug, we've eliminated 90% of the complexity of being able to take a UDT setting in your Ignition gateway and having that model appear automatically in the SiteWise service. And then for every instance of that UDT, that creates an asset, and then all other process variables are updated in real-time into the time series database. Now, that makes it accessible now to other people that wanna use that data in cloud services. So I'm gonna hand it back to Kevin, and he'll explain how the data that we put up there can be used in business and industrial applications. So Kevin, back over to you.

Kevin: Thanks a lot, Arlen. We had a couple of questions come in that are really timely here, so I thought that maybe I'd answer at least one or two of them, or at least pass one over to you, Arlen. So one of the questions was, "What do you have to simplify historic and live data acquisition over a data diode?" The data diodes are unidirectional gateways, that's another name for them. And basically, it's a one-direction push of data from one side of the network to another without bi-directional communication. The good news here is that MQTT Sparkplug, as mentioned, is a standard that is available for any technology company to implement. And one example that I know of on the data diode side, Owl Cyber Defense, which is one of the major companies that does data diodes, has MQTT Sparkplug as one of the supported protocols. So you can just feed things, and from one side, go right through the data diode and MQTT Sparkplug comes out the other side there. There are a number of other options there as well, we have a lot of companies that are using data diodes, but that's a really easy answer and solution for that if you're using these tools that we're talking about.

Arlen: Yeah, I'm very familiar with that solution, Kevin. And you're right, we work with Owl on that. And it is a really cool way. If you're looking at using data diodes, MQTT really lends itself well to that.

Kevin: Yeah. Thanks, Arlen. And then the other question I wanted to quickly answer here, and we're going to keep a couple of these questions for the end, but this one says, "There's no standard tools to leverage the Digital Transformation and IIoT requirements as there are multiple types of sensors, and each has its own limitations when it comes to process data. Do you have any platform where we can converge multiple technologies through different protocols?"

Kevin: This question came in about 15 minutes ago, so I think that it was before we started talking about this. But I just wanted to say, everything that we're talking about here is addressing that question specifically. So on the collection side, the different protocols that are spoken with different servers, with different technologies, that's all done on the collection side, and then that data and modeling puts it into a standard model so that you can do exactly what you just said, get it into a standard, move it through as a standard so you don't have to worry about all the different protocols. You certainly have to deal with them on the collection side, but as soon as you have those in place and you have the collection in place, that's cookie cutter, that's a model, you can roll that out for any similar sensors in the future and then have that feed right through the same process so that you do have standardization going forward, even though, as you say, on the actual device side, there's not a lot of standardization. But when you put this in place, it gives you that standardization across the enterprise.

Kevin: Alright. So just as important as collecting data is what companies do with it to empower the processes. This is another area where Ignition really shines. Ignition has a robust set of development tools that enable companies to create their own industrial applications, customized for their specific needs. Because of Ignition's interoperability, it's possible to create virtually any kind of business application and subscribe and publish data with the rest of the company, such as ERPs, CRMs, and other business systems.

Kevin: Ignition is really powerful for building industrial applications, so things like SCADA, HMI, IIoT, MES, as I've been mentioning. With Ignition, you can connect to all of your IIoT data, rapidly develop any kind of industrial application and instantly web-launch clients to virtually any device. Ignition can run as a web application or a desktop application, it's your choice. Ignition has powerful built-in tools for creating full-fledged systems. Ignition is also modular, so you can easily add fully integrated software modules for building industrial applications such as alarming, reporting, data streaming, and more, all inside the same platform. Ignition comes with everything users need to create any kind of application for multiple different display types. So if you're looking at desktops, industrial displays, HMIs, mobile screens, Ignition supports all of that.

Kevin: The designer creates a rich component library, and it makes that available for everyone, but it has easy data binding, it has powerful tools for drawing and scripting, and it has all of that integrated in that one integrated development environment. It's easy drag and drop. You can rapidly build and customize large projects, create custom graphics and animations. And the designers are unlimited, you can have one or two or five or 10 engineers that are all set up and designing things at the same time, and Ignition easily supports multi-designer setups. The designers are also free, there's no charge.

Kevin: Because of Ignition's modular platform, Ignition offers a high degree of customization. It's made up of individual core modules that are designed to work seamlessly together. You can really think of the modules like apps on your smartphone. Apps increase the feature set as you install them on your phone, likewise, modules increase the feature set or the toolset inside Ignition. Each module gives the platform powerful features to enable creation of industrial applications. And this architecture, what you're seeing right here, this software stack, really makes Ignition extremely flexible and scalable as individual modules can easily be updated and added to perfectly fit a company's requirements.

Kevin: Ignition also has an open SDK. So if you have programmers on staff and they want to do low-level programming, you can program your own modules. However, the toolset is intended to be feature-rich enough that folks don't need to do that, and it has all the tools built-in for companies. It's very rare that folks create a module, every once in a while, somebody will, or creating something to talk to a special protocol for a special device that they've created in-house or something like that. You can create your own drivers, you can create your own sets of logic inside there. But in general, Ignition has those tools to be able to build logic even without that SDK. That said, that SDK is open, 100% available, free. If you have programmers, they'll appreciate that. There are examples on GitHub, it's well-documented, and it doesn't require any cost to sign up or to access that.

Kevin: So let's take a look at a few apps that were built in Ignition. This is an app for San Bernardino County. You can see mapping tools, tank status, real-time levels, remote viewing of process variables and centralized alarm management there. These are all-mobile screens. This is a mobile app that they created. And this is an app for Ariens Company, which is really a quick example of OEE and production information aggregated by time, which includes downtime entries. This is one for Avery Dennison, it gives examples of managing logistics. And that's for the different lines that you see right there. And this one is used by the New South Wales Rural Fire Service. This is for tank levels and load requests. This is for fighting fire so they can see the different levels of water and return that are available at different airports that they can fly into. They go down to the tarmac, they load up, they take off again, and it helps them be much more efficient in terms of saving the forest and saving homes and everything that they're doing there. So these are some examples of applications that you can build rapidly in Ignition. There are thousands of different examples out there, and we'll share a couple more here in a few minutes.

Kevin: 'Cause Ignition is interoperable, companies can leverage the best analytics and machine learning tools as well to get an even deeper understanding of their data. Analytics are really crucial for getting real value out of Digital Transformation. As you probably know, being able to collect, gather, and transmit data in a structured way is great, but it doesn't have a lot of value unless there's a good way to visualize the data and garner insights. Data without context, data without analysis, is just data, and you're going to end up overwhelmed with that data. You need to get information out of the data, and getting information out of the data means taking a look at the data, analyzing it. If you have a good foundation of that data, like we've just been lining out, if you have data structures and data models, that makes getting information from that data much easier and much quicker. If you need the ability to get those insights and loop them back into your decision-making, you can do that now, too, and a number of companies are doing that in terms of closed-loop control and also providing some feedback to operators for suggestions on how to improve processes, how to improve performance, how to improve setpoints.

Kevin: One of the things that Ignition helps you do, it has built-in visualization tools, and it does have built-in machine learning algorithms as well, it has about a dozen of those. It's open platform nature. It really gives you the freedom to use not only the built-in algorithms but best-of-breed analytics and machine learning technologies as well. It's very flexible. And many industries are really adopting machine learning as well. One industry where we've seen a lot of that in the past few years is oil and gas. We've got a couple of examples. CSE ICON is one of our systems integrators, and they solved a number of problems with oil and gas with machine learning. For example, they had operating points for wells, optimizing and predicting artificial lift. Another integrator in that space, TIGA, has many other offerings: tank leak detection, decline curve analysis, predicting pipeline corrosion and suggesting where to explore, so the exploration inside oil and gas, basically, where to consider looking for oil based on past drilling information. Oil and gas has the reputation for being slow to adopt new technologies, but really, in this space, we're seeing that they're ahead of the curve, at least with the integrators that we have in that side of that space using machine learning.

Kevin: The culmination of all of this isn't really the machine learning and analytics, but the culmination is the full set of technologies here. You end up with that business and industrial applications that have access to that data that give you that insight, that might tie into the machine learning and analytics. It also gives you these structures so other things can tie into all of this as well. As Arlen was talking about, that pub/sub model, the publication and subscription allow for any system to tie into these data streams to make that available, have a single source of truth across the entire enterprise, and that data modeling gives you consistent standard data models that you're working with apples-to-apples comparisons for everything inside the organization.

Kevin: Now, what would this be without success stories? We wanted to talk to you a little bit about this, and part of the reason that Eric so graciously volunteered some of his time to be here today was to share with you one of the success stories that they have. We're gonna start with a project for Avery Dennison. Flexware is that systems integrator. And Eric worked on this and many other transformative products over time, so we'll go ahead and pass it over to you, Eric, to talk about this.

Eric: Thanks, Kevin. As the labor markets made it a little more difficult to hire and retain employees, we see more and more organizations that have been introducing automation into their logistics operations by using automated guided vehicles or AGVs for short and autonomous mobile robots. Avery Dennison is one of those. They expanded the production and warehousing capacity of its plant in Greenfield, Indiana. This included the implementation of a new JBT AGV system, that would manage logistics movements, such as transferring large rolls of paper label stock autonomously around the facility, feeding production equipment, stocking WIP areas, removing scrap material, and delivering finished goods to specific shipping areas. Avery Dennison needed the new system to integrate with existing facility systems and processes as seamlessly as possible, and that process involved a combination of movement events triggered both by automation systems and human operators. That meant that the solution required sophisticated business logic to ensure that materials were routed automatically to the correct destination, to coordinate with operators on human-operated vehicles, as well as with line-side operators calling for materials and to report all material movement to the inventory tracking system in Oracle.

Eric: At Flexware, we leveraged our existing solution accelerator built on Ignition, a toolset we've since named LIFT, which stands for Logistics Integration Framework Technology, and added additional capabilities to meet the challenges posed by Avery Dennison's implementation. We developed a new vehicle adapter interface for the JBT REST API using the WebDev Module and custom scripting, using the concept of an AGV mission to define source and destination locations. The existing mission dashboard was enhanced with picklist logic for the various lines and a mission-triggering system was added to provide workflow-like mission selection based on PLC tag values. Numerous configuration screens expanded the configurability and flexibility of the solution and all settings were persisted to accustom Microsoft SQL database. The data interface was developed to communicate with Avery's MES Oracle ERP layer to manage schedule coordination and inventory tracking.

Eric: The solution was developed to be highly configurable, and here we see an example of the configuration screen for what we call a mission leg. The mission leg is a foundational component of the system and represents a movement from a source location to a destination location. Missions may be made up of several legs, like if you needed to get from A to B and then from B to C, and each of those legs can be configured independently. In this case, this leg is configured for the robot to pick up material at the GF-1 unload location and take it to an intermediate location or decision point, which you can see here is defined as GF-1 Decision Point.

Eric: As it reaches the decision point, the JBT system reports back and solicits the LIFT system for a final destination. At that point, the system evaluates potential destinations within the configured location zone using sophisticated business logic, and in this case, that location zone is warehouse staging for GF-1. It finds a suitable spot to place the inventory, allocates the space for it, and tells JBT where to deliver the material. This screen is an HMI that was developed for one of the coders. The layout represents the physical layout of the conveyor as it moves material off the line, and on the screen, it's going from bottom left to top right. As the material comes off the line, the operator inspects the roll and is able to manage its status, marking it as either a good roll or something that may need re-work or something that maybe needs to be scrapped, and then when it gets to the location in the upper right, there's a location presence sensor that goes high, and when that PLC value goes high, because of a mission trigger that's configured, it will select a mission that is appropriate for that role, sending it either to the warehouse staging area or potentially to re-work or to scrap, or sometimes even to a line, if there's production needed, that that material is needed for immediately.

Eric: Once the mission is selected and started, the mission ID is populated in the upper right to let the operator know that a vehicle has been dispatched to pick up the material. For the result, Flexware developed the solution over a six-month period and partnered with both the Avery Dennison and JBT teams to implement the integrated solution into the production environment. With pretty limited training, the Avery Dennison team achieved complete customer ownership of the solution utilizing the full-featured configuration client to reconfigure existing missions as desired and add new equipment, vehicles and missions to the system as needed. And they've been able to continue to extend the solution to add new capabilities without having to call us all the time. The system manages Avery Dennison's autonomous vehicles, human-driven vehicles, production lines, a shipping area and an expanded warehouse area allowing Avery Dennison to increase logistics capacity significantly at the Greenfield plant with minimal additional manpower. Back to you, Kevin.

Kevin: Thank you so much, Eric. And I just love success stories like that and hearing about how folks are not only able to put so many different pieces inside their overall system, get information, get feedback from that and have some other transformation of their company, but also... You mentioned it right at the end, using an open platform allows them to also take over and have some ownership for all of this and not be necessarily tied to just working with a single integrator going into the future, and... Not to say that Flexware isn't great, Flexware is fantastic, we've worked with Flexware for a long time, and I'm sure that you continue to work with them from a standpoint of big projects or new additions, things like that, but it sounds like they're able to take ownership and to also do additions to the system on their own, and have that access and keys to the kingdom there inside the platform. So that was particularly insightful, I thought, at the end there, so thanks for sharing all of that. Very quickly, I'll go through these and... But these are just some of the names of manufacturers that are using Ignition, but each one of these has significant projects, and this is just a... It's a small snapshot, of course. We have many, many, many customers, thousands of folks using Ignition around the world, over 100 countries.

Kevin: And so we pulled out a few that might be interesting to the audience here. Atlas Copco, they have a solution that does production line management, tracks their information and has basically switched a number of things from paper tracking over to automated tracking and to computer-based tracking, application-based tracking, digital forms. JMA Wireless, they used Ignition for data acquisition, historical analysis, OEE product tracking, part testing, part tracking and reporting. State of Indiana has a program that they've set up as a partnership with the Indiana Economic Development Corporation and AWS as well, Amazon Web Services. Ignition is gonna be used in this state-run program, and it'll help get around 1,000 small to medium manufacturers engaged in Digital Transformation . As mentioned, it's partially funded by the state of Indiana, which is really nice for helping companies transform, maybe even if they weren't planning on it quite as quickly as they can now. JLG is using Ignition for data collection, machine control, remote alarming notification, reporting, and more. They used to get data points every four hours, and now they're getting them every 15 minutes. And Qorvo is an example in semiconductors. They're a semiconductor fab, and they use Ignition to pull data faster than they used to, improve machine connections, and make data available in ways that they didn't have access to it before.

Kevin: To understand why companies in so many different industries are choosing Ignition, I'll hit the main benefits of Ignition as your Digital Transformation platform here, and the benefits of making inductive automation a partner really in your Digital Transformation journey. As I mentioned, I've worked with hundreds of companies on their different journeys over the years, and we are happy to work with folks directly and work with integrators as well to help make those things happen, and provide advice, and really be a partner inside this space. Ignition's very different from a lot of other solutions that are on the market. As we mentioned, it decouples those intelligent devices from applications. IIoT can be built from the ground up inside the Ignition platform but also using open standards. I don't have the proprietary lock-in that you might have with other platforms. You don't get stuck with a certain set of technologies, you have open standards that anything can plug into, and it's easy to build those robust applications that were mentioned before. Ignition has a real strong focus on security, so we have everything from inside our organization. We have secure development training for our developers, we have industry-leading encryption support, so the same things that you use for signing into your bank account when you support those same technologies.

Kevin: Also, the most modern technologies that might have two-step verification that tie in with different identity providers, as they're called, and we have support for that across the board. We also have something called Inductive University, this is a website that's available, that is... That allows folks to log in and go through. It's 100% free. There are free videos that are part of this. Users pass online challenges to earn Ignition credentials, and we also offer a certification program for people to earn Core or Gold certifications. All of this, and with Inductive University, is really in an effort to help the business and help the industry by providing both software platforms and really the knowledge to help them turn their data into actions and their ideas into innovations. So Eric and Arlen, do you have any thoughts about Ignition's benefit to share here? And maybe we'll start with you, with Arlen, with you this time.

Arlen: So again, Kevin, from my perspective, and again, Cirrus Link has worked with Inductive on a lot of these solutions that you're talking about, and it's that notion of Ignition as a platform, it's that notion that you can leverage the tools on that platform, and you can come up with just about any solution. I'm always... It's incredulous to see all of the different applications in the markets that we're in, and every day we get another one we're going, "Oh, my gosh, I didn't realize if you do this, you can do this, and you can do this." So it's just understanding how to leverage Ignition as a tool and start on your Digital Transformation journey, just fix that one problem and start going from there.

Kevin: Thanks. Eric, over to you.

Eric: Yeah, as I said earlier, I really like it for both the depth of the capabilities and a lot of the things that you can do right out of the box, as well as the accessibility. You can download the Ignition trial and run it in a two-hour window and feel some things out and get off the ground running quickly and then continue to expand from there.

Kevin: Great, great. And just so we can get to some Q and A, I'll go ahead and wrap up here. And then we'll be able to answer some of the questions that have come in over time. If you have a question you've been sitting on, go ahead and type that in and we'll see if we can get to it. So to wrap up our message this morning here, Ignition really is an unlimited platform for really true Digital Transformation . It connects processes, people, and programs, like we talked about earlier, by facilitating free flow of information across your organization, it solves data problems that block innovation, gives you the tools to access more of your OT data and bring it together with your IT data. It empowers Digital Transformation through data collection, data modeling, publication and subscription, industrial and business applications, analytics, and machine learning.

Kevin: And Ignition also connects you to a whole ecosystem of other software solutions and hardware solutions and services to help you navigate your Digital Transformation journey. So I did wanna invite you to simply download Ignition and try it for yourself if you never have. You can just go to our website, you can download it from there. It'll give you the latest full version, it'll run inside a trial mode, and you can run that as long as you might like. It only takes three minutes to download and probably two minutes to install, so it's very quick to get going. I also wanted to invite you to register for our 10th Annual Ignition Community Conference, which we're calling ICC X. This year, for the first time, we're offering it in two different parts, there's an in-person piece in Folsom, California, and there's also a virtual event. In-person, it's September 20th through the 21st, and the virtual is October 3rd through the 5th. If you can come in-person, that's great. If you just wanna register for the virtual, that's fine, too. We're also doing a Build-a-Thon, and that's an exciting thing. We have keynote, Discover Gallery panels, educational sessions, workshops, vendor exhibits, networking, and more. So really, if you have a chance, go ahead, register now, either come for the in-person, buy a ticket or you can register for the virtual for free.

Kevin: And for those outside of North America, we wanted to let you know that we do have a network of distributors. So these distributors are available around the world. You can reach out to us, and we'll put you in contact with them or you can reach out to them directly, of course. We're happy to work with you, and they are all experts with Ignition. They provide local support and local language support as well, so it's great to have them as part of our reach around the world. And if you'd like to speak to our account executives, here are their contacts, and this is how you get a hold of anybody here. Of course, we've got general sales, email And I'll go ahead and ask a few questions here now that we just have a couple of minutes left, but I wanted to get to a couple of these. One is, "Will this webinar be available after the fact for sharing with others?" And the answer is yes, absolutely. So we're gonna send out a link that'll be on our website, it'll be available through multiple mechanisms actually, but yes, you'll be able to get this and if you wanna pass it around. We had a couple of people who asked that question, so that's the answer there. This one is probably for you, Arlen, this is, "I like the MQTT tool, but I have trouble proving to controls engineers why MQTT is so much better than OPC UA."

Kevin: It's interesting. They probably haven't seen a webinar like this so... I think that we tried to outline a lot of the benefits here pretty clearly, but Arlen, maybe you wanna answer that question.

Arlen: Well, it's definitely not an MQTT versus OPC UA. They all have their fit in a lot of the solutions that we've been talking about. We are seeing devices come out every day, new devices that support MQTT Sparkplug natively. So I think as we get into that, you just... I think you've got your legacy equipment and you're definitely gonna keep using OPC UA polling engines for that, but I think as things evolve, you're gonna see more and more adoption of MQTT Sparkplug going forward, and contact me if you wanna have direct conversations on how I can convince your engineers.

Kevin: Great, great. So this one is, "Can you please explain how data models are developed in Ignition?" That would be probably just explaining more or less UDTs. Maybe, Eric, over to you for that. I know you have a lot of experience in building efficient applications.

Eric: Sure. UDTs are a great way to do that, and you can basically build a structure that's deployable as specific instances that have that data model encapsulated. You can also do some modeling in Python scripting, and if you really wanna get advanced, you can go under the hood and build modules in Java as well, and that... Which is kinda what we've done with LIFT. We kinda went through that entire path that I just said, but lots of different ways to build your data models, and of course, you could also, as referenced here, build them in MQTT topic structures. Yeah, a lot of ways to do it.

Kevin: And then I know that we have... We probably have time for one more question here. There's one that came in part way through that I wanted to try to get to. It says, "I know Ignition has multiple connectors, but its capability for cloud environment and to connect to multiple cloud platforms is not clear to me. How can we have a secured connection of the OT to the cloud in real-time?" And so that's partially a networking and security question, is partly a technology question. So on the networking and security side, there are some security technologies built-in. Arlen, I'll let you talk about those in just a second here. On the networking side, of course, if you need to make that connection, you do have to have network policies in place and you have to have the communication path available. So there's normally a conversation that you have with your IT folks, there's normally a conversation that you'll have with your security folks to make sure that you're using best practices, but in terms of after that connection, it's possible the security that's built into that MQTT communication is something that's really nice to have, and in fact, it's necessary normally for even having permission to make those connections and do it in a secure way. So, Arlen, do you wanna just spend maybe 30 seconds talking about that?

Arlen: Sure. So if I'm making a connection... And one of the interesting things, if you look at all the cloud providers, look at Google, IBM, look at AWS, Azure all of them provide MQTT connectors. And why did they do that? The reason they did that is if I'm making a connection over MQTT from a facility outbound to the cloud, I don't have to open any ports in my plant. So that is the top thing of Zero Trust, is you're not gonna trust any of that, you're gonna make an outbound connection and no ports are gonna be open in the factory, and that's what part of AWS's Zero Trust platform is leveraging MQTT. Again, we can go into a lot more detail on that, please contact me for further details.

Kevin: There was one other item that came in that was not a question, but it was a comment that came into questions. It says, "No questions, but it was so cool to have a webinar from some industry titans. Very informative and cool. Thank you." And thank you, John, and thank you, Arlen, and thank you, Eric. I'll go ahead and say thank you to all the attendees as well. It's been a great webinar. Where to hear about the next webinar and our latest updates, do follow us on social media or sign up on our weekly newsfeed email. Thanks for sticking with us, and of course, if you're watching the recording after the fact, glad to have you watching that as well. Thanks for joining us here. Have a great day, everybody. Take care.

Posted on June 10, 2022