In manufacturing, quality is one of the most important features. Every production step must fit, every component must be checked. However, producers often discover errors only at the end, when the product has already been manufactured. Accordingly, the effort to rectify the error is high. Because the earlier defects are detected, the fewer production steps have to be undone.
Hengst SE produces oil filter housings in which several differently shaped seals are inserted. Automatically acquired images, which are also automatically evaluated (automatic visual inspection), are used to ensure that the seals have been correctly inserted into the recesses. If the gaskets protrude, it can happen in the production process that they slip in further assembly steps, get jammed between the housing elements and the assembly leaks.
Because there are different seals and surfaces, classic approaches to visual inspection meet their limits here. That's why the use of artificial intelligence (AI) is an obvious choice. But when using AI solutions, it is difficult to understand the AI's decisions. AI is therefore often a black box with opaque processes. Together, the cooperation partners Hengst SE and NFT automates GmbH therefore developed a solution for this problem.