The startup utilizes eddy current technology to enhance defect detection in carbon fiber composites, enabling the production of lighter and more efficient materials. This approach allows clients to create cost-effective carbon composites for applications such as aviation and renewable energy, improving resource efficiency in manufacturing.
Funding
$320K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
The increasing use of carbon fiber composites in industries like aviation, renewable energy, and part manufacturing is hampered by the challenges of efficient and accurate defect detection. Current testing methods are often destructive, semi-destructive, time-consuming, or require specialized facilities, leading to increased production costs and waste.
Solution
Eddytec provides a non-destructive testing solution for carbon fiber composites using eddy current technology. This approach enables fast, simple, and accurate defect detection, unlocking the full potential of carbon composites across various industries. By integrating with robotic systems, Eddytec's technology can be automated, significantly speeding up the testing process. The solution offers valuable insights through machine learning integrations and simple reporting, allowing for informed decision-making and improved resource efficiency in manufacturing. The technology eliminates the need for coupling agents, making it easy to operate and implement.
Target Audience
Eddytec's primary customers include manufacturers of carbon fiber composite parts, particularly those in aviation, aerospace, hydrogen pressure vessel production, and part manufacturing (e.g. prosthetics).
Features
- Non-destructive testing of carbon fiber composites using eddy current technology
- Up to 10x faster than current testing methods
- Automation-ready through integration with robotic systems
- Intuitive user interface requiring minimal training
- No coupling agent required for operation
- Machine learning integration for enhanced data analysis
- Simple reporting for actionable insights