Non-destructive image evaluation through AI-supported image evaluation
| German title: | Zerstörungsfreie Bildauswertung durch KI-gestützte Bildauswertung | |
| Acronym: | ZEBA | |
| Duration: | 1st October 2025 - 31st March 2028 | |
| Description: | The aim is to develop an AI-supported process flow that can be integrated into the manufacturing process and provides non-destructive information about the expected burst pressure of individual chips. Burst pressure is an important parameter for pressure sensors, as it determines the system safety of measuring devices and entire systems in the food, pharmaceutical, energy, and chemical industries. According to the current state of the art, the burst pressure can only be determined destructively on individual test samples. In addition to the sensor design, the quality of the silicon direct bonding is the decisive parameter for the burst pressure level. Research is being conducted into image property relationships, whereby certain non-destructive imaging tests allow qualitative conclusions to be drawn about burst behavior, but no physical-analytical simulation model for determining the probable burst pressure exists to date, meaning that quantitative statements are not possible. The aim of the project is to develop an AI-supported process flow that can be integrated into the manufacturing process and provides non-destructive statements about the expected burst pressure of the individual chip. |
|
| Funded by: | Federal Ministry for Economic Affairs & Energy |  |
| Project sponsor: | Euronorm | |
| Funding code: | 49VF250012 | |
| Contact: | Contact us about this project via our business unit MEMS | |
« back to project overview
