With the development of powerful real-time imaging modalities, the sector of minimally invasive interventions has grown massively in the last decades. Minimally invasive medical disposables (like guide wires), that are used for the navigation of instruments in the vascular system, play a very important role in this field because the easy and reliable navigation of the medical devices used in minimally invasive interventions is one of the key aspects for the success of such an intervention. Currently, only a limited spectrum of navigating devices for these interventions is available - defined by the medical device manufacturers. The main goal of the project "Openmind" is to develop a new production system that will bring individualisation to the field of minimally invasive disposables and will hand the power of device specification to the end-user: In the future, the "Openmind" system shall give the physicians the opportunity to define their dream device on-demand, in small quantities and at reasonable cost. This will help to make minimally invasive interventions even more effective and efficient.
For this purpose, two challenges need to be met: creating a production process that is highly flexible and economic at the same time and assuring that the quality standards and requirements of medical device manufacturing are still fulfilled. The partners of the project "Openmind" develop solutions to solve these issues. In order to reduce production cost, the future process chain will be able to perform all necessary processing steps for the manufacturing of minimally invasive disposables in a continuous and thus economic manner whilst providing maximum flexibility for individualisation of the product. The system will machine the parts in the running process and the product will not be cut to length until the very end of the process. The system will be equipped with a powerful data management tool to ensure product quality and to fulfil the requirements of medical device manufacturing. Dedicated software will be developed using data mining strategies adapted for small series production.
In the project the following systems will be developed by the consortium: