List Making: If You Can’t Beat ‘Em, Join ‘Em

Welcome to 2018! It’s a new year and list-making has broken out all over the place. Lists of the biggest political gaffes, biggest sports upsets, most watched YouTube videos and, of course, the list of notable persons who passed away this year. I am very grateful to have, once again, avoided making that list!

Since we are all in list-making and list reading mode, I thought I’d start 2018 with a list, too. My list is the top 10 myths of the Internet of Things (IoT) and Industrial Internet of Things (IIoT).

Myth 1: EtherNet/IP and Profinet IO are Cloud-Ready IIoT Communications Protocols
I’ve heard this a lot from the ODVA (Open Device Vendor Association) and the PI (Profinet International) trade associations for the last few years, but I think it’s finally been put to rest in 2017. Both the ODVA and PI tried to pass off EtherNet/IP and Profinet IO as “cloud ready,” implying that you could connect them to the cloud and use them in IIoT applications. In 2017, they seemed to understand that most of us weren’t buying it so, hopefully, we’re past that sort of nonsense. Profinet IO and EtherNet/IP are excellent technologies for moving I/O data between field devices in a factory and a programmable controller. Nothing more and nothing less.

Myth 2: The Internet of Things is New
Not even close on this one. If you’ve been in manufacturing long enough to break for lunch, you should know we’ve been moving machine data to back office systems since the first programmable controller was deployed. If you’re thinking this is new in commercial applications, have you heard of something called an automated teller machine (ATM)? What is an ATM but a device for moving data from remote locations to a central server? Seems like an Internet of Things device to me!

Myth 3: MQTT is a Viable IIoT Technology
I know many of you don’t want to hear this; however… MQTT (MQ Telemetry Transport) is fine for quick proof-of-concept developments, but it’s not a secure, reliable or flexible strategic technology you should use in critical IIoT applications. MQTT is simply a transport protocol. It has no inherent security and requires an out-of-band, external mechanism for transferring data configuration.

Myth 4: IIoT is About Moving Data
Even though a lot of people think IIoT is about moving data, it’s not! IIoT is about making more intelligent business decisions. That isn’t necessarily true in the consumer world where the objective for an IoT system can be to improve the quality of a person’s life; but in manufacturing, we need to make more intelligent use of resources, be more efficient, nimbler, faster and more responsive to our customers. That’s what the Industrial Internet of Things should really be about.

Myth 5: Picking the Right Technology Is Key to IIoT
No, technology isn’t even near the top of the list of key aspects of IIoT. That was true 25 years ago when all we had was serial buses like Modbus RTU, DeviceNet and Profibus DP. But today, the key to IIoT is a viable business model; knowing how you can use data – what’s available and what you might possibly get – to enhance your key performance indicators. It should be just like any other improvement you make to the factory floor: how much are we going to spend (more than you think); how will we achieve a return on that investment.

Myth 6: The IIoT Infrastructure is Already in Place
It’s actually not; there are limits to what we can do with cloud services. Once we start equipping every motor, actuator and sensor with IIoT capabilities, there won’t be enough cloud storage for all that generated data. We’d have to cover the planet with server farms to store it all! The IIoT infrastructure needs to evolve to the point where data can be automatically curated and analyzed locally with only summary data transmitted to offsite storage. GE Predix’s, Microsoft Azure and the rest are only the first generation of the IIoT infrastructure that our manufacturing plants will need.

Myth 7: The “Have Raspberry Pi – Will do IIoT for Food” Myth
I love the Raspberry Pi for quick demonstration projects, but as a long term, supportable technology on the manufacturing floor, it’s much too limited. The Raspberry Pi is a very underpowered IIoT device, unable to perform the curating, analysis and summarizing of data that will be needed in tomorrow’s IIoT projects. It’s the equivalent of designing your next automation device with an 8-bit processor.

Myth 8: The IoT Chaos is Only Temporary
I predict this will never get sorted out. IIoT is destined to become fragmented with oodles of competing standards. The market is too big, the applications too numerous, the vendors too disparate to ever coalesce around a group of standards, let alone a single standard. Just last month I ran into a major consumer products company that is basing their IIoT efforts around Kafka, a technology named after a Russian poet!

And if you’re a device manufacturer making drives, robots or even simpler devices, the landscape is going to be especially chaotic and complex. You will need to think about what customers you’ll serve and how you’ll use devices, services, applications, hardware platforms, standards groups, business models, geographies and even other users to serve them. It’s going to be a lot harder than just adding an EtherNet/IP or Profinet IO to your device.

Myth 9: IIoT is Hard to Do / IIoT is Easy to Do
These are both myths and truths at the same time, depending on your perspective. IIoT is easy to do if you just want to move some data and you aren’t really concerned about security, meta data, longevity or Return on Investment (ROI). Just moving data is easy (see Myth #3).

IIoT is hard to do if you want to do it right. That means securing the data, executing a project that completes on schedule, using hardware and software components that are viable for the long term and making money (ROI).

Myth 10: The Open Source Myth
I’m not a fan of open source in the manufacturing world, though I’m admittedly biased – we sell software that is also available as open source. I know far too many ‘gotchas’ in the manufacturing world. I see technologies like OPC UA that are extraordinarily feature-rich and extremely complicated to deploy. I see significant risk in going with an open source project in a complicated manufacturing environment where millions of dollars can be at stake. I see it as risky to not have a partner that can assist you when the dog poo hits the fan. Open source is a good strategy for demonstration projects, but if you are going to go open source, make sure you fund your own internal expert in that technology that can manage it for you.

One thing is clear to me: the manufacturers who have clarity of purpose (ROI) and develop the flexibility, agility and speed to adapt IIoT are going to gain competitive advantage in the marketplace!