You could say that the world is relatively familiar with industrial revolutions.
It's less than two hundred years since the arson protests against the Spinning Jenny threatened the progress of the cotton industry, so it seems relatively commonplace for growth to be greeted by a little skepticism.
However, the Internet of Things (IoT) made an oddly seamless entrance into people's homes; arriving in the form of Alexa, Siri, and Google Assistant. And most people don't even know what drives these technologies.
Sure, Elon Musk has prophesied doom, but, in general, AI and the IoT are finding their place with relatively little fanfare; setting down the groundwork for the Internet of Things to take its rightful place in modern manufacturing.
You could say, then, that IoT in manufacturing is a silent revolution.
The Industrial Internet of Things (IIoT) is already here. It's no longer a future trend in the workplace. This is now. And this is how the IIoT is already transforming modern manufacturing.
When it comes to the supply chain process, it's not unusual, relatively speaking, for businesses to work in the dark.
Each stage of the production process takes time; but there's an awful lot of dead time between the completion of one task and the initiation of another.
IIoT data promotes smarter working with tools that offer visualization of each and every process; building the path towards more efficient methods because the inefficiencies become glaringly obvious.
IIoT visualization offers a holistic view of assets and can predict and prevent machine failures - maximizing productivity time by avoiding production delays.
Now, we're really heading into sci-fi territory!
A Digital Twin (DT) is one of the latest innovations in IIoT technology — and a core functionality you should expect of all good IIoT platforms.
A DT is a complete replica of your real-world production line. Using simulations, the DT can test the lifespan of physical assets, developing better versions of your product, all while identifying inefficiencies in present production processes.
Plants using DTs can predict where physical assets are likely to run into maintenance issues, preventing machine failure that can halt or slow down production.
Physical assets that benefit from DT simulation can range from wind turbines to airplane engines.
In fact, using CAD-style simulations, incorporating VR and AR platforms, any machinery can be mapped and analyzed in a controlled environment.
Self-Healing, Autonomous Systems
Through machine learning, IIoT technology is becoming capable of intelligently identifying and addressing issues without requiring human intervention.
For example, Duke Energy - a Florida-based power holding company - claims that their grid system can automatically reconfigure itself wherever power is lost in the home.
Using sensors across the entirety of its power-grid, outages can be detected and mended in seconds.
Previously, an outage caused by a lightning storm - for example - could take several hours to resolve because engineers need first to identify the root and impact of the issue.
This is all achieved in seconds with autonomous systems that can heal themselves.
The implications for industry are huge - allowing employers to focus on other mission-critical functions while the machines take care of themselves.
It wasn’t that long ago that the perception of the factory floor was one of a dirty, noisy, dangerous workplace where life-changing injury was not an unlikely outcome.
This image has caused real issues in attracting new talent into the work pool - especially Millennials, whose expectation of the workplace is very different from that of our forefathers.
That’s certainly changing.
Manufacturing is, of course, a potentially dangerous place, but with IIoT sensors and connected devices, it's possible to detect malfunction that could cause injury in environments that once would have created substantial hazards.
IIoT has made it possible for firms to monitor — through video analysis or by kitting employees out with sensors — anomalies and hazardous situations that can cause harm.
For example, Laing O’Rouke - an international engineering firm - have introduced smart helmets to monitor their employee's health in hot climates.
One of the hazards of heat stroke is that if you start to feel the symptoms, you already have it.
So, the smart helmets have been designed to monitor heart rate, temperature, humidity, and other life-sensitive readings to help identify and prevent heat stroke when working in hostile, desert environments such as in Qatar.
The art of increasing employee productivity has never been a particularly exact science.
The microscopically dissected activity of employee productivity has been under the management microscope for years. However, most attempts to continually monitor progress tend to meet a diminishing return because most processes in the past have required manual input and buy-in from workers. Until now.
There's a growing range of machine monitoring technologies that use the IIoT to help monitor continuous activity while encouraging engagement from workers in the form of gamification.
For example, Canadian machine monitoring firm, FreePoint Technologies, has developed a suite of IIoT smart monitoring systems that give real-time productivity data on the macro level, as well as at the micro.
Their systems allow individual workers to monitor their own progress and compare their output with the contribution of their peers. Not only this, but machine monitoring and learning facilitate absolute synchronicity over the production function of the entire factory.
Managers can monitor productivity from anywhere on the planet that has an internet connection — providing distance decision making, ensuring that deadlines are always met.
And while being consistently observed could sound intimidating to the average employee, the productivity data produced gets used for incentive schemes and to demonstrate competencies during staff evaluations.
Buy-in from employees is achieved through game-play style competitions, reaching specific milestones for special rewards.
The IIoT is transforming the way that modern manufacturing runs production; in ways that already feel like sci-fi.
It's changing the way we work now - increasing efficiencies, productivity, engagement, and safety, so that manufacturing can continue to thrive.