AI-based inline measuring equipment for electroplating technology

Challenge

In contrast to predominantly mechanical manufacturing processes, suitable and sufficiently cost-effective measurement technology does not yet exist in industrial electroplating. The product quality of coated components can therefore only be determined once the end product has been finished. At this point, it may no longer be possible to determine which parameter deviation(s) during the course of the production process is/are responsible for a reduction in quality. This is particularly problematic in the case of safety-relevant components – e.g. fastening elements – and, in particular, if the defect – e.g. material embrittlement caused by hydrogen created through electroplating – is only revealed during technical application.

Solution

The innovative measurement system is intended to combine a system-adapted, cost-effective and industrially-suitable in-situ analysis of the process baths with the AI-based evaluation of measurement data from process and system control, status parameters of process units, and other relevant data. Intelligent machine-learning algorithms that are to be developed should enable individual adaptation of the measurement system to the respective coating processes.

Added value

In this project, an AI-based metrological system solution for industrial electroplating is being developed, with which all process parameters relevant for the digitalization of electroplating production processes can, for the first time, be provided cost-effectively and with sufficient accuracy. The core issue is therefore the replacement of a major part of the otherwise very expensive chemical analytics.