The industrial internet of things (IIoT) is transforming industrial practices all over the globe. It is helping businesses to harness new technologies to increase productivity, manage their infrastructure and better meet strategic goals. It’s being used to help manufacturing plants grow, revolutionize agricultural practices, streamline supply chains and radically change how we approach business.
(Source: Pixabay)
A story of connectivity
Since the 2000s, the internet has dramatically changed how people live and work. One of its main characteristics has been connecting people — allowing communication via chat, messaging, VoIP texting and video calls. Think back, say, 20 years ago — the internet has been transformational to our communications.
Computers (or technology, more broadly) have been at the heart of that transformation. Technology has primarily served as a pathway, or conduit, to enhanced collaboration between people. It has changed how we discuss issues, share ideas, organize information, make decisions and support each other. It has been a mediator — a tool to human endeavors.
But with the advent of the IIoT, a new trend is rapidly emerging as Industry 4.0 unfurls. It is increasingly the connectivity between computers and machines in their own right that is driving transformation. The web is much more than about connecting disparate people. It is now about computers themselves communicating to drive change.
Of course, technology is still a tool to support our goals. But its nature is qualitatively different from what it was. It works for us but is increasingly autonomous and self-sufficient. The IIoT is a manifestation of this phenomenon, and the opportunities it already presents for manufacturing businesses are vast.
(Source: Unsplash)
The growth of the IIoT
Several new technologies have made the rise of the IIoT possible in the past decade:
- Better and more affordable sensor technology
- Wireless networking with the growth of the cloud infrastructure
- The advancement of big-data analytics
Sensors can capture myriad real-world measurements in real time: temperature, pressure, size, climate conditions — endless possibilities. Sensors capture the raw material (data) that computers can use to model, monitor and refine processes.
Wireless networking allows all of these data points to be collated and processed by powerful computers. The cloud means data can be gathered almost instantaneously from disparate locations — anywhere in the world — and sent wherever it needs to go. Cloud computing is crucial in enabling the latent value of data to be realized.
Big-data analytics churns through this raw material — the data — identifying patterns, opportunities or concerns. This data fuels machine learning, enabling computers to refine processes and trigger actions. More workflows can be automated, optimized and streamlined. For example, feedback (e.g., a particular setting tweak) can be returned to the source machines almost instantaneously (thanks to the cloud). In short, analytics makes data actionable.
What is the IIoT?
The Industrial Internet Consortium (ICC) defines IIoT systems as: “The internet of things, machines, computers and people, enabling intelligent industrial operations using advanced data analytics for transformational business outcomes.”
Notice the inclusion of “people.” While the IIoT is qualitatively more advanced, it is still a tool. It must be employed appropriately to maximize its advantages. That requires strategy and careful planning. What “transformational business outcomes” does the business wish to achieve? How will they respond to insights revealed by data analytics? People are critical in deciding these sorts of matters.
The IIoT and manufacturing
The IIoT allows manufacturers to become ever smarter, and that can translate to higher productivity, greater efficiency and improved delivery of other business goals. It is not surprising, then, that a significant part of digital transformation for many manufacturing businesses is about turning to the IIoT.
There is no one-size-fits-all model for this, however. Every business will need to identify its approach to embedding the IIoT. For example, some will be able to invest more than others (and so make a longer initial step). Every business will have a different infrastructure upon which to weave sensors and other technologies — raising unique challenges at each site.
Strategic objectives will also shape the journey. Some firms may focus on raising the output of their factories. Others may be concerned with reducing operational costs. And still others will focus on minimizing their environmental impact or improving the safety of their plants. Every IIoT journey will be unique.
(Source: Unsplash)
How manufacturing benefits from the IIoT
To finish, let us consider just a few of the main benefits that the IIoT can bring.
Enable greater automation
The very essence of the IIoT supports moves to automation. It enables machines to take on ever larger tasks: monitoring, analyzing and refining — a feedback loop between the manufacturing equipment and the computers that process all the data points.
In this way, automated processes can respond to many other factors. Are there holdups elsewhere in the factory? Is there a supply-chain issue? Might changing weather conditions have an impact on operations? Automated processes can become more complex — and responsive to a broad range of factors.
Improve operational efficiency
The IIoT can support optimization in many areas of manufacturing. The data can provide an accurate picture of everything happening across the plant (and beyond). That, in turn, can be analyzed to identify efficiencies. That information can be shared with workers on the floor or sent directly to the equipment.
A manufacturing operation can thus fine-tune aspects of its work. For example, optimization can apply to power consumption, work rate, raw material consumption and equipment settings. And each of these represents a potential efficiency — reducing overheads.
Asset maintenance
Sensors across the factory floor can monitor equipment performance in real time. Anomalous data points can be identified and flagged — helping to avoid serious problems. For example, temperature or pressure sensors may indicate an error; the component in question can then be checked and fixed.
This type of predictive maintenance is now commonplace. It helps factories avoid downtime (due to broken machines). Moreover, it is quicker and cheaper to fix problems identified sooner. In some sectors, this sort of predictive monitoring can be life-saving.
Asset monitoring like this can also support longer-term infrastructure management. For example, it can be easier to determine when equipment needs replacing or deeper checks.
(Source: Unsplash)
Prepare for Industry 4.0
Digital transformation will mean different things to every business around the world — from eFax in Canada to cybersecurity and remote working. But for any business with a manufacturing wing, their approach to the IIoT will be a significant characteristic of their journey. For manufacturers, it will be the essence of their relationship with Industry 4.0. How far will they go embedding connected machines, machine learning, automation and big data into their operations? That question will grow in volume as we move through the 21st century.
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