Manufacturing technology
Know anything about medical manufacturing – the high distribution costs, the need for speed and efficiency – and this rush towards robotics makes sense. But though factories the world over rely on machines to make their devices, they equally exploit technology to check them for problems. This isn’t particularly surprising. With FDA fines for faulty equipment sometimes rising to eye-watering figures – a few years ago, one Minnesota company was fined $27m for supplying hospitals with defective heart devices – companies are under immense pressure to ensure their products do what they promise. And in a world where factories often stretch across dozens of production lines, it’d be too expensive and time- consuming to check thousands of devices by hand. Enter ‘vision systems’ – the broad name for a range of automation technologies, together ensuring everything from syringes to artificial hips reach their patients in prime working order. They’re now so central to the inner workings of device development, in fact, that ‘automation’ is often just as likely to refer to vision systems as to the manufacturing process itself. Nor do the technologies underpinning these platforms show any sign of slowing down. Backed by AI and machine learning, inspection protocols could soon become even more sophisticated – even if manufacturers probably shouldn’t sack their human staff just yet.
Grand visions It’s tempting to imagine that vision systems developed together with general automation – but seen in a certain light, they’re much older. As long ago as the 1960s the algorithms that modern vision systems rely on were first being honed – while image coding began to be investigated in the 1970s. Whatever their origins, it’s clear that vision systems are now familiar sights on factory floors across medical manufacturing. “We have one medical line, for example, where we have 48 vision systems on it,” says Ken McClannon, a technical business unit director for Jabil Healthcare Pharmaceutical Delivery Systems. “Now there might be 250 stations on the entire line – so 20% of the stations on the line are vision systems.” With those kinds of numbers, it’s no wonder McClannon says his work really encompasses “automated assembly and testing” as opposed to mere assembly – a fact that other experts are happy to explain. As Anil Bharath, professor of Biologically- Inspired Computation and Inference in the Department of Bioengineering at Imperial, at Imperial College London puts it, the “fast through-puts” vital to modern manufacturing could be impossible with cumbersome manual checks, while plumping for the occasional spot check might put an operation’s quality control (QC) at risk.
Medical Device Developments /
www.nsmedicaldevices.com
But if device safety explains the broad importance of vision systems – shadowed by the fact that outstanding QC can increase company profits by up to 15% – their real ubiquity can be understood from the variety and complexity of modern medical devices. In Mexico, to take one example, industry giant Medtronic has a factory boasting 4,000 workers making everything from catheters to stent grafts. At the same time, the increasing sophistication of modern medical devices is forcing firms to invest in robust vision systems. At their most technical, devices like eye implants might have hundreds or thousands of tiny pieces, each needing to be flawless in shape and length. The size of devices also makes vision systems a necessity. With defects sometimes the diameter of a single human hair, it’s unsurprising that manufacturers rely on machinery to catch issues humans could never see. In fact – and as the name implies – perhaps the easiest way to understand vision systems is as all- seeing eyes, programmed to peer over conveyor belts and warn workers of problems. To make that happen, platforms are equipped with special lights, often in contrast to the surrounding environment, ensuring that the machines can spot scratches or dents. That’s typically echoed by investing in the strongest cameras – with McClannon claiming that resolutions are getting “higher and higher” all the time.
“You can use specific wavelengths, in terms of the colour of light you use and so on, and use multiple different lighting strategies to inspect different features of a device”
Ken McClannon
Rage against the machines As McClannon’s last comment suggests, vision systems are constantly being sharpened. And if higher resolutions are one area of work – the latest systems can sometimes provide zoom up to 21 megapixels – the Irishman is equally enthusiastic about other improvements. That’s true, for instance, in terms of lighting. “You can get very specific about how you design your lighting for the application,” McClannon explains. “You can use specific wavelengths, in terms of the colour of light you use and so on, and use multiple different lighting strategies to inspect different features of a device.” In a similar vein, McClannon describes the higher memory of modern vision systems, meaning that platforms are cheaper and faster than when he started in automated manufacturing some quarter century ago.
More than that, however, perhaps the most revolutionary development in vision systems is
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