The Internet has finally come into its own in the cloud age. It was never going to be just about webpages on screens; it was meant to form the bedrock connecting digital services and platforms to allow people to make, buy, share, and say things easier.
In the same way, the Internet of Things (IoT) is evolving into the form that could have the most impact. However, as far back as 2016, a report claimed consumers didn’t want more devices, so the IoT utopia where all devices talk to each other may never come to pass.
Instead, industry is likely where the IoT will come into its own. It’s becoming a critical piece of Industry 4.0, with companies across manufacturing, logistics, and construction already embracing the expanded tool sets of analytics, big data, digital twins, and more.
Welcome to the age of the IIoT—the Industrial Internet of Things.
The IIoT works on the principle that each device, machine, or system in an operation collects, reports, and shares performance data. This includes outputs, inputs, speed, load, maintenance status, sales and location data, and whatever else applies to each component.
The data could relate to a belt on your factory conveyor, the size of a database in a customer relationship management platform, or the core temperature in a nuclear reactor, but it's all going to be critical for tomorrow's workforce.
Several layers make up IIoT environments:
All interfaces, from computer and mobile screens and smart surfaces to augmented-reality (AR) glasses and virtual reality (VR).
The apps and software that collect IIoT data and transform it into insight about the operation.
The protocols and devices used to transmit information, from tools on the factory floor that are hardwired together to cellular data from the field.
Devices are the hardware doing the reporting across the organization, from CNC milling machines or 3D printers to production-line robots and transport or packaging equipment.
There are already plenty of IIoT builds making waves. Imagine an architect retrofitting an office building. Live data from sensors in the building detect traffic flow, lighting, and air-conditioning usage, which can continuously flow into your building information model and digital twin. Refit requirements are updated on the fly.
In manufacturing, sensors attached to production-line assets can report errant vibrations back to a general maintenance database, enabling quick identification for fixing or replacing a failing part, long before it brings the entire line or factory to a grinding halt.
In oil or gas, market fluctuations in pricing or demand can feed directly into business risk metrics, directing drills and trucks to respond and adjust their capacities in real time.
Just as developers test a website behind a subdomain or experimental server before going live, the home market has been the unofficial proving ground for the IIoT.
In the home IoT, the principle of having multiple devices communicate seamlessly across a single domain is the same. The industrial sphere differs in the kinds of devices, the systems that drive them and which they report to, and the sheer scale.
The consumer IoT is where device and system manufacturers need to fail early and often, because by the time such platforms and tools reach the industrial sector, they need to work the first time, or the whole movement will stall before it starts.
The best way to explain how the IIoT works in practice is to look at some examples.
The Rachio smart lawn-watering system takes data from recent and future weather forecasts to know when and how much to water, automatically. Scaling that up to golf courses and office parks could have a big impact on water usage while making sure plants and lawns get the best coverage for conditions like soil quality, slope, sunlight, and weather.
Broader examples can be found in the following industries:
The IIoT’s beachhead in heavy industry so far has been reducing maintenance costs. Complicated manufacturing production lines traditionally replace parts according to a schedule: Pieces of the workflow are taken out and replaced after they reach an assumed viable lifespan. Even if a part would, when examined, clearly have lasted longer, the enterprise incurs the expense of a new one. It’s like paying a kind of insurance to keep products coming down the belts uninterrupted.
But with sensors attached to every lathe, power supply, and articulated effector, preventative maintenance changes. Acceptable performance parameters can be established for each tool. IIoT data can report on them constantly, warning automatically when something’s getting too hot, too worn, is drawing too much power, or isn’t targeting precisely enough.
The cost savings are twofold. First, the manufacturer gets the entire lifespan out of a device rather than junking it simply in accordance with a schedule, when it may still work fine for a long time. Second, the manufacturer can design its workflow to temporarily bypass the offending component, requiring minimum downtime to replace it and keeping the operation running at full speed.
In construction, the IIot excels at staff and asset tracking. If companies manage multiple sites at once—and material supply, weather, or staff availability affect capacity—trackers affixed to vehicles or uniforms can give an at-a-glance picture of everything’s and everyone’s location.
Between $300 million to $1 billion worth of equipment is stolen from construction sites across the United States every year. For those who fall victim, it will be much easier to track IIoT-connected assets.
Worker safety is also a huge issue in construction, with more accidents and fatalities than in almost every other industry. If injuries occur too often in a particular area (reported by IIoT data), closer inspection might reveal the reason, giving the firm the chance to address the issue.
Designing a part, a component, or a device is more efficient and cost effective with the use of precision 3D design that includes methods like generative design.
For example, one might take the 3D files of a prototype design and send it to a 3D printer. After testing, the specs can be sent from the 3D-printing process back to the digital file, updated and ready to send to live production.
Connecting systems yields many benefits, giving businesses:
Old or legacy systems that were not designed to connect with other platforms or machinery can be very expensive to retrofit or reprogram. IIoT tools are built to be easily customizable and deployable in any workflow, with minimum disruption.
Sensors or transmitters affixed to everything—from raw materials to retail packaging—can give a supercharged view of assets across the supply chain.
Such insight allows for immediate reaction to market conditions. If there’s a shortage of raw material, one can find a replacement or hold out for supply without a big financial hit. If a celebrity is seen tweeting their love of certain products, manufacturers can instantly ramp up production to meet new demand.
Signals can be collected and collated from every point across production, manufacturing, or distribution, whether that’s device performance on the factory floor or sales and online chatter about specific wares. Using the IIoT to put all that together effectively gives an immediate, ongoing, macro view of the business.
The ability to change quickly means that the IIoT lets manufacturers innovate and pursue growth at the speed their business or sector moves, keeping ahead of the demand curve. It also lets them scale up without disrupting live production environments. New systems and platforms have IIoT principles baked in; production or workflow shifts can be executed seamlessly and quickly.
IIoT devices can report on their own performance and can also monitor and track the quality of outputs, spotting defects or mistakes when they happen—before a disappointed customer unboxes them after purchase.
IIoT-connected devices for monitoring oil and gas can report leaks or high pressure. In manufacturing, connected devices can give managers an overall view of where workers are in relation to potentially dangerous equipment. Better yet, they let operators perform tasks remotely through VR or remote robot control, well out of harm’s way.
For all the IIoT’s promise, a slipshod IIoT deployment has the potential for to disaster. Just like the internet in general, higher connectivity between systems means more entry points for nefarious actors and cyberthreats.
A bigger IIoT environment means more devices, databases, and software are connected, and it all increases the threat profile. The entire business network is only as strong as its weakest point: Just a single attack vector can let methods like distributed denial of service (DDoS) attacks cripple operations, costing money to find and mitigate the problem—as well as lost profits while operations are offline.
Some of the most vulnerable attack surfaces in IIoT deployments include:
When staff and partners from across a supply chain access IIoT data, credential management is critical: Who’s accessing what and when, and do they have permission? Password management is also crucial, and session or timeout management will close the loop.
The proverbial hacker sitting outside someone's house in their car using their wi-fi is applicable to the manufacturing or construction industries, too. Open ports or other network vulnerabilities might give cyberthreats access to operations at the network or domain layer.
Data in transit throughout IIoT networks might not stay within the organizational borders in today’s connected supply chain world, so strong end-to-end encryption standards must be applied before a single byte is generated.
“Cloud creep” is an increasing issue as staff use their personal devices in IIoT workplaces. Data critical to an organization’s domain might end up anywhere if an operator decides to send a file through a third-party service. There are also vulnerabilities in employees’ apps that can give cyberthreats another back door into the whole network.
The IIoT is in its formative years, and more widespread adoption will cement standard practices and increased innovation in the area. Some of the most important future trends will be:
With a completely data-driven workflow, it’s easy to build an accurate digital representation of an operation and everything in it—also known as a digital twin.
A digital twin gives the ability to prototype workflow changes and test them in a simulation, among other functions. It also enables the entire operation to run remotely, with operators using technology like VR or mobile to drive components from anywhere in the world.
The IIoT is a facet of big data. Although it initially seems counterintuitive to share information about outputs or results with competitors or industry associations, all that information can combine in the cloud to give anybody who needs it a clearer picture of where the industry is going and what it needs.
Trade agreements, government industrial policies, measurements about greenhouse gas emissions and sustainability will all be more precise and informed.
For those who thought cybersecurity was an important area, it’s just getting started. Every device and interface that connects to a domain is a potential new vulnerability. Implanting security right in the IIoT’s DNA is going to be the biggest technology science of the next cyber age.
Legacy systems are black boxes, but as they’re gradually replaced by smart applications and platforms built for interoperability, there will be an increased need for systems to ensure they integrate properly.
Enter artificial intelligence (AI), which will run the workflow intelligently and take all the signals and data the process generates, using them to further streamline and improve those processes without the need for human involvement, especially in facilities that use robotics.
Most of the activity in additive manufacturing, which began in the industrial sector, has moved away from its zetigeisty consumer sphere of a decade ago and returned to where it will offer the most value. Prototyping products or workflow components is cheaper, faster, and more sustainable with additive manufacturing. And the data goes both ways, with process tools suggesting the best result and the process informing them of how to work better in turn.
Despite the hype, consumer IoT applications still have a long way to go. To be ready for industry, those applications have to move beyond the unbalanced minimum viable product (MVP) implementation that has informed development so far.
Think of a large house that’s been turned into a consumer IoT testing ground, with 150 connected devices, 18 different systems, and five different networks. Many issues can result from this configuration if, for example, an IoT security device was meant to protect other devices from malware but couldn’t cope with even the relatively small number of devices on the network. This leads to a hassle of troubleshooting and, ultimately, the system’s failure.
Now imagine trying to implement that in a more complex setup, like a data center’s cooling management system, which needs to deploy hundreds or thousands of sensors and actuators. Industrial settings won’t tolerate continual triage and management for all of these devices and their interconnections. They just need to work.
For the Internet of Things to add value to industry, it needs the following:
Many consumer IoT applications are cool but unnecessary. They demonstrate what the technology can do but don’t address a real human need. For those that do—like security, energy conservation, and health—the benefits need to outweigh the costs, including the time and attention required to install, maintain, and troubleshoot.
A minimum viable product that focuses too heavily on minimum (features of a product) and too lightly on viable (workability of those features) has informed the first generation of too many IoT products—and that’s not good enough for the IIoT.
This article has been updated. It originally published in March 2016.
After growing up knowing he wanted to change the world, Drew Turney realized it was easier to write about other people changing it instead. He writes about technology, cinema, science, books, and more.
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