In my current position as a project manager, I have responsibility for the manufacturing process and how it works with the Internet of Things (IoT). I must understand how these items interact with information technology and the growth of our company.
The IoT is one giant network made up of hundreds of millions of smaller networks, each consisting of computers, vehicles, home appliances, and manufacturing equipment. These devices are all embedded with electronics, software, sensors, actuators, and network connectivity devices that enable them to connect and exchange data.
This article isn’t the place to go into the IoT in depth. What is important for my purposes here is to acknowledge that IoT proliferation is essentially unstoppable — it’s happening in every industry, institution, business, and home. Wherever you find human activity, you’ll find aspects of the Internet of Things.
Twice as nice
One technological advance making the IoT even more functional and fluid is the “Digital Twin” process, in which a digital replica of a physical asset, process or system. In a recent YouTube presentation, IoT expert, Chris O’Connor, explains that a digital twin is “the ability to make a virtual representation of the physical elements and the dynamics of how an Internet of Things device operates and works.”
A digital twin is way more than a blueprint or a schematic. Instead of it being a picture, “It’s a virtual representation of both the elements and the dynamics of how an Internet of Things device responds throughout its lifecycle. It can be a jet engine, a building, process on factory floor, and much, much more.”
The advantages of pairing the virtual and physical worlds enables us to analyze data and monitor systems to head off problems before they occur, prevent expensive downtime, and develop new opportunities. In short, we can plan for the future by using simulations that accurately predict what would happen if a simulated virtual catastrophe were to occur in the physical world.
For example, if we were to hook up a million sensors to a motor or engineering system, creating the code that perfectly maps out what that system is currently doing, we could monitor anything, or test anything, using that system. This is the essence of a digital twin.
Connecting to reality
Manufacturing is one of the first areas to benefit from digital twin technology. DTT is reducing costs, enabling crucial systems to be placed into maintenance (with accurate predictions on how doing so will affect downstream and related systems), and leading to less downtime and better production methods. Components can be tested and measured inexpensively enabling engineers to design better products at lower prices.
Perhaps the most significant impact of digital twins, however, will occur in the realm of computer networking. Don’t forget, after all, that the IoT is made up of networks.
In the process of setting up a physical network, one must include monitors and monitoring points to detect and prevent potential problems. Unfortunately, a network designer can’t think of every possible scenario in which something could go wrong, and testing for these myriad events is both costly and a generally inexact science.
Imagine, on the other hand creating a digital twin of your network. Now, while it’s reporting in real time, you can see how it reacts to everyday traffic and scenarios. Even better, you can freeze the digital copy run various scenarios to see their effect on the system. The big advantage is that you don’t have to failover real-world locations or real-world servers or systems — no costly downtime.
So, how exactly does a digital twin operate within a network environment? In a network, a digital twin has three areas: Build, Operate, and Enhance. In the Build phase, you can optimize traffic on your network, to direct clients to your failover SaaS environment or even another location.
You can do this without putting down or even touching your physical production environment. This is the Holy Grail for network engineers, who are anxious during table-top exercises that test partial or total outages.
The Operation phase puts your digital infrastructure in the palm of your hand with remote monitoring, daily adjustments, and even artificial intelligence adjustments. You can predict issues that are likely to arise, sometimes months in advance.
Enhance is the last phase of a digital twin. This is where you merge all your data analytics into a cohesive package and use it to drive business decisions. With the advent of AI and Big Data, the decisions can even be made for you. The day isn’t far off when your Amazon Web Services or SaaS application will auto-adjust physical equipment on your manufacturing floor to save time and money.
For networking’s future and IoT, everything will need to move to an IPv6, rather than an IPv4 technology. This will allow the broad expansion of IP addresses for everything — and I do mean everything. I recently attended a conference where they displayed a honeybee hive, in which an IP micro-dot was placed on each bee. The bees didn’t seem to mind, and the collection of data was phenomenal.
Established idea, new applications
Digital twin technology isn’t new, having been around since 2002, and it is the IoT that is making it a cost-effective solution. Forbes called digital twins one of the Top 10 technologies of 2017 and predicts widespread adoption in 2018:
“When you start hooking up IoT endpoints, devices and physical assets to data sensing and gathering systems which are turned into insights and ultimately into optimized/automated processes and business outcomes, as we do with the Industrial Internet of Things (among other things), there are quite some new possibilities that arise, to say the least.”
That is a big claim, but not hard to believe if digital twins are hooked up correctly. But, as Hamlet said, “There’s the rub.” It’s not an easy road to becoming an expert in digital twin technology.
One big reason for that is that, at the moment, there are no certifications for working with the tech. Practitioners typically do a lot of reading on the topic and acquire what experience they can. One way to gain experience is to work with companies like Splunk and Salesforce IoT that produce software designed to search, monitor, and analyze machine-generated big data via web-style interfaces. Building a digital twin is still the best way to gain proficiency.
Oh, the places you’ll go
It isn’t a stretch to imagine that, with bio-patches and IP addresses, we could even make digital twins of ourselves. Just think, with enough data on yourself, you could predict a cold or heart attack, or project how much longer you would live if stopped smoking, started exercising, and dropped a few pounds.
Forbes estimates that, by 2021, more than half of the top manufacturing firms will employ digital twin technology. The future is incredibly bright for anyone jumping on this bandwagon. Since the technology can start small, scale to whatever you need, and grow your bottom line, there is no reason not to jump on.
Whichever way digital twin technology goes, and as fast as it comes, I recommend getting into it with an open mind and an excitement for growing your business.