Is IoT Platform Software Needed in Manufacturing?

Jan. 2, 2024
Most IoT platform investments have been handled by IT for enterprise use. But manufacturing operations have distinct data needs for which IoT platform software is well suited and need to be involved in the decision-making process.

IoT platforms are generally understood as being an application or a service that enables a  company to connect all the various “things” in an Internet of Things ecosystem. In  manufacturing, these “things” tend to be devices and software. The idea behind IoT  platform software use is that data from all these “things” can be aggregated, analyzed and  shared for a better overall understanding of the manufacturing operation. 

To get a better handle on how manufacturers should approach the idea of using IoT  platform software—and its relevance to industry’s digital transformation—we spoke with  Steven Ward of Emerson for a recent episode of the “Automation World Gets Your  Questions Answered” podcast series. The Q&A that follows features a few highlights of that  discussion. You can access the complete podcast via the link above in this paragraph. 

David Greenfield, Automation World
Why should manufacturers seriously consider the use of IoT platform software?

Steven Ward, Emerson
Think about HMI and SCADA. If we look at traditional large manufacturing plants, they've  had these large systems for monitoring in place for years. If you look at a process plant, it  might be a DCS (distributed control system). But where people have always struggled is  connecting remote assets. So, if you've got a fleet of assets that are widely distributed,  that's really where IoT comes into play because IoT  is about getting data from those edge  devices wherever they are into central systems that go beyond HMI/SCADA and into how to  optimize the plant. And the typical things that people want to do are to increase efficiency  and reduce unplanned downtime.

Whether you have a machine or process, you need to understand how that machine or  process is running. You need to establish a baseline. You need to understand how well the  machine or process can perform when it's operating correctly and then, by collecting data,  you can then analyze its current performance and compare that against the baseline  performance and you can then see if there is a problem. 

With those data you've collected, you can then do more detailed analysis. It might be a raw  material problem. There might be issues with running the machine outside of its normal  parameters. It might just need some maintenance. But until you've collected that data and  started collating that data, you don't know. That’s what an IoT platform can address. So, that's the promise of an IoT platform—collecting the data, making it available and then  using its analytical capabilities to improve operations.

David Greenfield, Automation World
The initial Automation World reader question that prompted the topic of this podcast was  about assessing IoT platforms for vertical applications. Are there key differences about IoT  platforms when it comes to implementation in different industry verticals?

Steven Ward, Emerson
Yes, there are differences that manufacturers need to be aware of and those differences  tend to come down to domain expertise. Does your integrator understand your industry?

I have encountered this working across multiple industries. Different industries have their  own terminology. Some industries have their own particular requirements or particular  issues that they consider to be more important than others. That's where a user needs to  take a bit more care when it comes to IoT platforms. It's not so much about the technology,  it's more about: Does the person who's implementing this understand what your specific  issues are?

Take the automotive industry for example. A lot of automotive optimization is about making  as many vehicles per hour as possible and then optimizing the price of those vehicles. I've  worked with various automotive manufacturers in the past and what they want to do is get  as many cars manufactured as they can. And, for the production cost of each car, to make  it as cheap as possible. Even just saving a few cents per vehicle, though it doesn't sound  like much—but when you multiply it over multiple lines, multiple plants and the hours in  the day, the days in the week, the weeks in a year—it results in huge savings.

But if you are life sciences manufacturer, it's less about the productivity. Although  productivity is still an issue, it's more about validation. You need to make sure that what  you're making is absolutely conforming to your original plan or design or recipe, and you  need to be able to document that. 

Having said this, I think for most IoT applications it's more about monitoring rather than  control. You need to be aware of your particular requirements and whoever's providing your  solution needs to understand your industry.

David Greenfield, Automation World
When it comes to software platforms in general, they're usually more of an IT project than  an operations technology (OT) product. But with IoT platforms, the connection of plant floor  systems into the platform means that OT clearly has a stake in this process. How do these  IoT platform implementations typically play out across IT and OT in a manufacturing plant?

Steven Ward, Emerson
The biggest difference for me between IT and OT is that OT is very focused on speed. We  have systems that are running with the response time of a few seconds at most, but in  some cases the response time is in the milliseconds. So OT often has very high-speed  response requirements and that results in a larger amount of data. With a gas turbine, for  example, you can be collecting megabytes of data per second, and IT isn't necessarily  familiar with that sort of data collection.

There are also differences in terms of cybersecurity. Traditionally, OT people haven't really  worried about cybersecurity because they've always thought of their systems as being air  gapped, that is, not connected to the Internet. I've seen many OT systems which are  supposedly air gapped, but they were connected in some way or other to the enterprise  network. IT, of course, is much more concerned about cybersecurity.

And I think this is where IT and OT should be converging because OT wants to have their  particular performance guarantees and they need to be able to explain to the IT team what  that performance means and how much data there is. But equally, IT has the expertise to  keep these systems secure and, in some cases, to simplify configuration.

David Greenfield, Automation World
Considering those differences you just referenced, do you have any recommendations that  OT personnel should be sure to ask about any IoT platforms that are being assessed by the  IT department beyond the real time data handling capabilities you mentioned?

Steven Ward, Emerson
If IT are involved in the project, they may not understand how disruptive these systems can  be to OT operations. So the OT team needs to make sure that any changes that are made do  not interfere with their operations. 

For many organizations, productivity is key, and even a few hours of downtime can be  extremely expensive. So if the IT team is doing anything that disrupts OT operations, that  needs to be prepared and planned for upfront so that it minimizes any potential loss of  production. Of course, this can work the other way too, because we don't suddenly want  the OT team flooding the IT network with data and crashing the IT network.

That's why it’s very important for OT and IT to communicate to make sure that they  minimize any disruptions.

David Greenfield, Automation World
Considering your history of work with different manufacturers across industry, how far  along would you say industry is in terms of IoT platform adoption today?

Steven Ward, Emerson
Well, I think IT has dominated the investment here so far. But I think manufacturers need to  be aware that their primary purpose is to make something.  So whatever the output of your  plant is, that's what you do and you need to make that product as efficiently as possible to  the required level of quality. 

Many manufacturers don't have that good of a connection between IT and OT systems. You  might get an output from an ERP system, for example, that says I want you to make this  product on this machine. It does the planning, but it might be that that machine isn't best  suited to make that particular product. Maybe it can meet the quality requirements, but  maybe it can't meet the throughput requirements.

So, I think that's where there's a lot of room for improvement by manufacturers—to start  gathering data from their machines or processes and start matching them to the levels of  quality and throughput they need. And that's a big benefit IoT platforms can bring is by  enabling manufacturers to understand the capabilities of their machines and processes.