Robotic automation28 December 2023
When it comes to upgrading the suite of technology operating on the factory fl oors of medical device manufacturers, getting it right can be tricky. Between historically high investments costs and challenges around education and implementation, that’s especially true when it comes to robotics and automation. Yet if these difficulties have traditionally limited the ability of smaller companies to embrace the power of robots, things are changing fast. Andrea Valentino investigates, along the way speaking to experts across the sector.
These days, Becton, Dickinson and Company (BD) isn’t really in the same league as Medtronic or Stryker – but modern medical manufacturing would probably be impossible without it. In 1898 and at the cost of just $40, the American firm acquired a half interest in a patent to produce all-glass syringes – a striking new invention in the Victorian age. After honing their craft for half a century, BD would then push the technology even more dramatically. In the 1950s, supporting a new anti-polio vaccination campaign, it mass-produced around a million disposable syringes – one of the first times in history a single medical device was produced at such a scale.
Over the intervening decades, mass production has become a staple of medical manufacturing, hardly surprising given the scale of the industry. According to work by the WHO, there are some two million kinds of medical devices on the world market, divided into around 7,000 generic groups, which together represent a market worth over $530bn. It goes without saying, meanwhile, that this insatiable demand can only ever be achieved with mass production – and automated mass production at that. At any rate, this is reflected in factories themselves, with so-called ‘fixed’ automation, in the form of conveyor belts and other 20th century innovations, now common from Shanghai to Stuttgart.
Despite this preponderance, however, it’d be wrong to imply that device production lines are perfect. Developed for specific products, stamps can’t simply be tweaked to new devices, which is hardly ideal in an age where flexibility and scalability are so important. More than that, traditional automation can sometimes be unreliable, with operators unable to spot faulty equipment before it breaks – a situation that naturally hurts both profit margins and patients themselves. Amid these concerns, it makes sense that manufacturers are increasingly embracing the immense power of robots, leaning on genuinely autonomous machines that can take an active role in crafting new devices. There are, of course, cost and training challenges here, to name but two. But get implementation right, and robots could eventually transform the sector just as radically as BD did back in the 1950s.
Automation and robotics are two manufacturing terms that are sometimes conflated. But as Dr Howie Choset warns, they’re fundamentally different ways of manufacturing. The former, the Carnegie Mellon University professor explains, encompasses stamp presses or welding stations, “fixed” technologies that can’t be reprogrammed. Carsten Heer, of the Frankfurt-based International Federation of Robotics, agrees. “Classic machine tools,” he says, “need much more time to adjust the change for the production of a special item – or are even unable to switch at all.”
That’s a far cry from robots. Boasting malleable arms, which can quickly be given new digital commands, they’re far more versatile than traditional automated production lines, especially when they can be dismantled and reassembled elsewhere in a facility. As Heer says: “This flexibility allows companies to produce even small batch sizes for a broader number of customers in a very short time.” Nor are these merely theoretical benefits. In the US state of Minnesota, for instance, Tegra Medical doubled throughput after investing in a trio of manufacturing robots, freeing up 11 workers to focus on other tasks.
With these strengths in mind, you might imagine that robots are invading factory floors wherever medical devices are made. Yet the statistics tell a different story. The UK, for example, boasts a mere 23,000 industrial robots, translating to just 101 for every 10,000 flesh-and-blood employees. And though that proportion is higher in more tech-savvy countries like Japan, you similarly get the impression that, as far as medical device manufacturing is concerned, this technological bounty is unbalanced. For if the giants of the sector are rushing ahead with their own robotic investments – twin-armed ‘YuMi’ robots have, for instance, supported manufacturing at Johnson & Johnson factories since 2015 – smaller firms have traditionally struggled to keep up. As Choset puts it: “Most medical devices are made with fixed automation – there really aren’t robots.”
Economics has typically been one barrier here. Though prices have certainly dropped in general, the most complex manufacturing robots still cost around $400,000, while kitting out a whole warehouse could set a firm back as much as $4m. That dovetails with the cost of education. In one 2020 survey, 46% of UK workers stated that the financial burden of training prevented them from securing new skills, while the fact that 99% of all British companies are SMEs presumably means that their bosses haven’t been able to chip in either. And beyond all that, Jeff Burnstein argues, is the difficulty of appreciating how new automated machines will actually impact workflows. “What’s the best tool for the job?” asks the CEO of the Association for Advancing Automation, a major American trade association. “I mean, you don’t want to use a robot just to do it.”
How can these stumbling blocks be overcome? It may sound trite, but one answer arguably revolves around fully appreciating exactly what robots can do. For if they are indeed more versatile than the production lines of yore, that’s because of the complex algorithms that underpin them. And if that means they can easily be given new commands and converted, say, from making catheters to pumping out heart monitors, digitalisation can equally make the manufacturing process more straightforward. Trained on vast data sets, after all, robots can hone their skills over time, ensuring that finished products always reach industry standards – not least given the best machines now boast accuracy rates up to 0.001mm.
In a more general sense, Burnstein suggests that the competency of systems like YuMi drastically reduces the risk of human error from the factory floor, another potential barrier to quality products. Especially for dull, repetitive tasks – “grinding and polishing” are the two Burnstein pinpoints – he says that expecting total discipline from a human production line is asking for trouble. Once again, there’s clear evidence this is happening in practice. Since it leant on robotic support, to give one example, Tegra Medical has seen the number of rejected devices drop to just a couple each day. It helps, too, that the algorithms robots rely on can keep workers abreast of their own status, making maintenance planning easier while also providing vital information on those all-important workflows.
Given all these advantages, it’s unsurprising that the overall cost-benefit analysis for investing in robots is improving all the time, while higher demand means that initial purchase costs are diving too. As work by Statista has found, the average cost of industrial robots could drop to as little as $10,856, compared to almost $70,000 in 2005. And for medical device manufacturers eager for a more flexible business model, ‘robotics as a service’ is an increasingly popular option too. Allowing factories to hire equipment for limited periods, for example when tasked with manufacturing a specific device for a couple of months, this approach promises to bolster ROIs further still.
With all these advances, it’s no wonder that the market for robots in the manufacturing space is growing at speed: Mordor Intelligence predicts that the field will be worth some $40bn as soon as next year. Nor does the sector show any sign of slowing down. “Industry 4.0 is the next generation concept for the benefits of using industrial robots,” is how Heer puts it, and it’s hard to disagree when you consider what the most sophisticated robots can do. Quite aside from training themselves, or warning managers when they need to be maintained, that’s obvious when it comes to ‘collaborative’ robots. Working dynamically with human colleagues, they can sharpen the manufacturing process even compared to regular robots. At one American medical device manufacturer, for instance, these ‘cobots’ are being tasked with transporting delicate parts for human inspection, even as they place sterile wipes into containers for people to use.
“What’s the best tool for the job? I mean, you don’t want to use a robot just to do it.”
As this last example implies, robots shouldn’t necessarily always be left entirely to their own devices. To that end, Bunstein advises any company eager to embrace robotics to first hire a systems integrator. “[They] can help the end user spec out exactly what’s needed for the project,” he explains, “whether it be a lot of robots, fewer robots, and different technologies with it. It’s understanding what’s the most efficient way to produce the product you’re trying to do.” To put it differently, and like with BD’s revolutionary work almost 100 years ago, the point of any new technology is to get results, and to what extent robots are necessary to obtain them should always be open to debate.