Nowadays I’m trying to get my mind around AI, and figure out all the things I can do with it; but there’s another buzzword around, this one is ‘hyperautomation’. Today, it’s not smart manufacturing, but ‘hyperintelligent automation’. Please forgive me for thinking that’s what IIoT did. Anyway, I thought I would try and make sense of all these terms, and find out how they differ from automation, and if hyperautomation is part of AI and ML or the other way around, and where IIoT comes in, or gigafactories, or lights-out factories. Or is this yet another amazing new technological development? So here goes.
It’s clear that automation is the carrying out of a repetitive task without human intervention. It typically occurs on a smaller scale than hyperautomation, and involves separate jobs. An example would be robotic process automation (RPA) − a robot that can perform low-level repetitive functions based on rule-based processes, for example a welding robot.
Hyperautomation, on the other hand, is a combination of advanced automation technologies like generative AI, ML, natural language processing, digital twinning, data analytics, predictive maintenance algorithms and more, that automate processes without human intervention. From what I can see, hyperautomation is the concept of leveraging all these new technologies and automating everything in an organisation that can be automated – basically if it moves, you automate it. One description of hyperautomation I saw is that it’s RPA on steroids. Another is that it’s the automation of automation. The end goal is to automate as much of a task as possible, while allowing human workers to focus on other jobs that require creativity, judgement, and emotional intelligence.
IIoT at scale
I found it more difficult to decide if IIoT is part of hyperautomation, or the other way around. One school of thought is that hyperintelligent automation is a driver of IIoT; but eventually I decided that IIoT is the enabler, arising out of the convergence of OT and IT.
I remember when not very long ago we used to publish articles on how the machines are talking to each other. Hyperautomation needs manufacturers to think on a greater scale, and this is what’s driving the adoption of the IIoT technologies we already have. Complex automation is only possible in digitally interconnected systems. Gartner has listed hyperautomation as one of the top ten strategic technology trends of 2023, and believes it is shifting from a nice-to-have to a matter of survival for many organisations because it has the ability to eliminate outdated work processes, which are a top workforce issue.
Whatever you call it, many manufacturers are already dabbling in hyperautomation in preparation for a scaled-up IIoT because simple,
task-based automation doesn’t deliver the cross-functional results that they are looking for. Many of the examples I found are clients of Motion Control or have featured in our stories − companies like Siemens, ABB, Rockwell Automation, Fanuc, Schneider Electric, Festo and Honeywell. As an example, Schneider Electric automates the process of creating, labelling, documenting and organising switchboards. Human interaction is eliminated from the process, apart from data input and the physical installation of the finished product. In South Africa, we have some world-class industries such as the automotive, and food and beverage, and they are on the way to hyperautomation.
The benefits are pretty much the same as we heard when IIoT first came in: optimised processes, increased efficiency, and improved overall performance. So are the caveats. The explanations that jobs won’t be lost, they’ll just be different and more satisfying, are no different.
Avoid the traps
One of my favourite Bill Gates quotes is: “The first rule for a technology used in a business is that automation applied to an efficient operation will magnify the efficiency. The second is that automation applied to an inefficient operation will magnify the inefficiency.” There is a fine line between elegant networking and a tangle of hyper-automated systems − excessive automation.
Elon Musk discovered this in 2018 when the production line for the Tesla Model 3 came to a complete halt for four days. Musk said the plant became a manufacturing nightmare, with its complex network of conveyor belts struggling to manage production, and instead resulting in bottlenecks. Businesses can take digitalisation, connectivity, and artificial intelligence to an extreme without understanding fully what they hope to achieve.
Anyway, I have come to the conclusion that the road from manual to automation to hyper-automation is a continuum, and each manufacturer has its place on the scale, whether it’s a small factory creating lots of jobs or a Tesla gigafactory.
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