Approach to implant monitoring and data processing with digital implant lifecycle management
Abstract Reducing implant failure rates is a primary research objective, involving the development of monitoring methods, new treatment options, improved manufacturing strategies, and innovative implant designs. The goal is to enhance product efficiency across generations by using information from p...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-99975-w |
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| Summary: | Abstract Reducing implant failure rates is a primary research objective, involving the development of monitoring methods, new treatment options, improved manufacturing strategies, and innovative implant designs. The goal is to enhance product efficiency across generations by using information from previous iterations to improve patient outcomes. This paper aims to create an information management framework for implant-related data to enhance lifecycle monitoring. Strategies from product lifecycle management, condition-based maintenance, and the digital twin are applied to medical implant monitoring. The proposed digital implant lifecycle management concept records and processes data throughout the implant’s lifecycle, from design and manufacturing to use and disposal. Implemented using an XML-data structure in simulation software, the concept focuses on manufacturing and monitoring, using total knee arthroplasty as an example. A simulation study demonstrates that the digital twin of the implant can simulate various manufacturing scenarios to optimize process parameters, reducing planning efforts for individual implants by up to 28%. The presented concept significantly improves implant and patient monitoring, enhances communication among stakeholders, and allows for scenario simulations to predict implant behaviour and improve future generations. |
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| ISSN: | 2045-2322 |