Technology Category
- Analytics & Modeling - Digital Twin / Simulation
Applicable Industries
- Healthcare & Hospitals
Applicable Functions
- Product Research & Development
- Quality Assurance
Use Cases
- Digital Twin
- Virtual Reality
About The Customer
Medtronic is a renowned global manufacturer of medical devices. Their products are used worldwide in various medical procedures and treatments. One of their products is the medical stent, an expandable mesh that is inserted into a patient's artery to keep it open. The design and production of such a device require precision and rigorous testing to ensure its safety and effectiveness. Medtronic is committed to improving their products and processes to provide better healthcare solutions.
The Challenge
Medtronic, a global leader in medical device manufacturing, was facing a significant challenge in the design and validation process of a new medical stent. The stent, an expandable mesh inserted into a patient's artery to keep it open, required meticulous design and rigorous testing. Traditional methods of computer-aided engineering (CAE) and virtual simulation were not fully utilized within the industry due to the slow verification process for often microscopic components. Medtronic was seeking a way to not only improve the design of the stent but also to speed up the validation process, ensuring a faster time-to-market and better performing products.
The Solution
In response to this challenge, Altair ProductDesign collaborated closely with Medtronic's engineers to develop a baseline model of the new stent. They assessed the design for structural characteristics such as stiffness, stresses, and fatigue performance. An optimization process was then developed to enhance the product's performance. By morphing the baseline model, five different geometric shapes were created, and sixty design variables were identified. These variables were fed into Altair's optimization software within HyperWorks to determine the best possible design for the stent. This innovative approach allowed for a more efficient and effective design and validation process.
Operational Impact
Quantitative Benefit
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