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MEDICAL

AI-Assisted Inspection of Implant Coatings

Smith+Nephew is ten times more productive with AI

Smith+Nephew is a London-based medical technology group specializing in bone and tissue reconstruction, wound healing, and joint replacement. At the site in Aarau, Switzerland, hip shaft prostheses are coated, among other things. An AI-supported software solution in combination with a light microscope is used for quality inspection. The ZEISS solution delivers the results within a few minutes thanks to automated image segmentation.

ZEISS solution inspects implant coatings automatically

More than 400,000 hip and knee prostheses are manufactured in Aarau each year. A large proportion of these are coated in five state-of-the-art vacuum chambers at temperatures of up to 20,000 degrees Celsius, either purely with titanium or with titanium and hydroxyapatite. The latter is a bone substitute that improves or stimulates the ingrowth of the bone follicles into the porous prosthetic surface. 

The required thickness of the titanium and hydroxyapatite layer in a so-called POLARSTEM for hip reconstruction is between 155 and 305 micrometers. ZEISS light microscopes have been used to check layer thickness ever since the group began coating implants in Aarau. In 2022, the medical technology company in Aarau, which employs around 15,000 people worldwide, started working with a new light microscope, ZEISS Axio Imager.Z2m.

AI-assisted image segmentation

Until now, measuring the layer thickness required a trained eye and a lot of human interventions. Without AI assistance, the analysis process therefore takes 45–60 minutes for a POLARSTEM. The process has been ten times faster since Smith+Nephew started using the new light microscope. With this one-click solution, a comprehensive protocol with values for layer thickness and porosity is available after just five to seven minutes. This has two advantages for Smith+Nephew: Operators can now use more of their working time for other tasks such as taping the implants. In addition, potential manufacturing problems can now be identified more quickly.

Measurement process by AI-assisted image segmentation

This drastic acceleration of the measurement process is made possible by AI-assisted image segmentation. Operators now only need to align the sample and start the ZEISS ZEN core software – everything else is automated. “It couldn’t be simpler,” says Stéphane Monod, responsible for quality at the Smith+Nephew’s Aarau site. “And no matter who examines this sample, the measurement results would always be the same.” This is another advantage, not only for medical technology companies.

Unlock AI-powered image processing

Experience enhanced efficiency in complex image analyses with ZEISS ZEN core, now automating segmentation and classification for both light and electron microscopy. The AI-based software meets stringent industry standards. Seamlessly transfer your workflow, utilize high-resolution imaging, and access deep-learning analysis routines – all within ZEISS ZEN core!

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Equipped for the future

The Senior Manufacturing Quality Engineer is also enthusiastic about the AI-assisted ZEISS solution for another reason: “We are also equipped for future standard requirements with the ZEISS solution.” This is because, in addition to checking the coating thickness, the porosity of the applied titanium and hydroxyapatite layer is also determined. This is a characteristic value that implant manufacturers will have to demonstrate in the future to comply with the ISO 13485 standard.

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Stéphane Monod, Senior Quality Engineer at Smith+Nephew in Aarau

"A good coating of the implant is important so that it can grow in well and last as long as possible."

Stéphane Monod
Senior Quality Engineer at Smith+Nephew in Aarau

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More on the topic of AI-driven inspection

As this success story shows, AI's role in inspection is crucial. Curious about the current possibilities and how AI can enhance your inspection process? We spoke with Christian Wojek, Head of AI at ZEISS Industrial Quality Solutions, about how AI is shaping the future of quality control.

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