Sensor- and app-based validation of process and product quality for effort-reduced certification of personalized medical devices - Saviour

Key Info

Basic Information

Duration:
01.02.2021 to 31.01.2023
Organizational Unit:
Chair of Production Metrology and Quality Management, Model-based Systems
Funding:
German Federation of Industrial Research Associations (AiF)
Status:
Running

Research partner

    • IPH - Institut für Integrierte Produktion Hannover

Contact

Name

Anna-Lena Knott

Research Assistant

Phone

work
+49 241 80 20600

Email

E-Mail
 

Final Report

The final report will be available shortly from IPH or FQS.

 

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Under the European Medical Device Regulation (MDR), 3D-printed patient-specific medical devices will be subject to the same rules for approval as medical devices made using conventional manufacturing processes as of May 26, 2020. The strict safety requirements and lengthy approval procedures pose major methodological and economic challenges for manufacturers of individual medical devices, especially SMEs. Proof of process capability can only be transferred to the 3D printing process to a limited extent, since a large database consisting of measurement data of the same quality characteristics is required in order to make valid statements regarding process quality. However, this contradicts the innovation of 3D printing, with which each medical device can be individually adapted to the patient and produced in quantity 1.


The goal of the Saviour project is to develop an app that enables the real-time monitoring of process parameters to assess product quality and detect potential sources of error in the process. The knowledge gained can be used for process validation and optimization. In this way, a lack of methodological knowledge regarding process validation and lower personnel capacities in SMEs can be compensated.

By combining process-integrated sensor technology and quality models built via machine learning, process progression can be predicted and faulty production processes can be aborted at an early stage. With the monitoring of critical parameters and the increased understanding of the process, as well as the inclusion of historical data, the causes of errors and optimization potential can be uncovered automatically. The process data and the associated interpretations are documented for constant proof of process validity.

The app strengthens the competitiveness of SMEs by:

  • the root cause analysis and risk assessment is simplified,
  • process optimization potentials are uncovered
  • reducing testing efforts and using resources more efficiently, thus lowering manufacturing costs, and
  • enabling continuous proof of process and product quality for the approval of medical devices.