PHARMACEUTICALS
‘Getting pass/fail results on things that used to take days or weeks to program using traditional vision, you can now do with five or six images’
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wearer. “Before, they just used human inspection so for sure it affected consistency and had some human error,” he reveals. Until recently, the transparency of contact lenses made implementing machine vision- based detection a challenge in terms of accuracy and consistency. “But Teledyne Dalsa’s machine vision solutions for this purpose are based on user-friendly, low- cost iNspect embedded vision software and hi-resolution Genie Nano cameras.” Tese high-speed, low-noise global shutter CMOS cameras are ideal for fast and fine- detail inspection tasks, even when dealing with transparent objects like contact lenses. Another example is pill inspection.
Straight after manufacture, pills are fed onto a conveyor that gently rotates the tablets as they pass to confirm their features are correct in terms of dimensions, surface texture, shape, colour and labelling, and to ensure there are no surface defects. Until recently, this was left to humans, as machine vision solutions could not cope with the visual complexity of the scene, often flagging false positives and missing damaged pills. But AI-powered systems are now taking
over this laborious and tedious work. Cognex’s In-Sight D900 vision system is a CMOS camera embedded with a full suite of deep learning tools ideal for this application. Trained on images of defect-free tablets taken from various angles, it detects any pills with anomalies, while leaving the rest to continue through the production process. In-Sight D900 is part of a growing
trend towards sophisticated AI solutions. “Human-like AI judgement is becoming the modus operandi,” summarises Deats. “Traditional human judgements like ‘is it a bubble or is it a blister that makes it a non-conforming product?’ or ‘is it a scratch or actually a hole in the package that compromises what’s inside of it?’ are very tricky for conventional vision systems, and even humans, but not for AI machine vision systems.” Zhu agrees, offering his own example. “Feature analysis techniques can be used
Teledyne Dalsa’s iNspect software being used to check for empty capsules and leaked powder in blister packs
to qualify the concentration of a colour for a pharmaceutical ingredient, or the texture – for example, if the surface is smoother or rougher,” he explains. “Before, conventional vision algorithms have had difficulty tackling something with complicated textures, but with AI technology and deep learning, which we have been working on lately, this becomes very possible.”
18 IMAGING AND MACHINE VISION EUROPE AUGUST/SEPTEMBER 2023
Slow adoption Despite these benefits, take-up for advanced AI machine vision systems has been slow in the pharmaceutical industry. One reason is that the very standards that make machine vision such a good fit with the pharmaceutical industry also drag out the testing and verification processes for new products. Validating automation products is also particularly time-consuming and expensive due to the raft of documentation needed and the involvement of various stakeholders. As a result, if a pharma company finally manages to install an
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