DIGI4PLAS

Limited process control in plasma coating

Modern PVD plasma coating systems mainly record control-related process parameters such as coating duration, power, gas flows, bias voltage, and, where applicable, temperatures on the substrate. However, the key plasma characteristics present inside the coating chamber, such as the density of chemically reactive radicals or ions as well as electron density and temperature, which ultimately determine the coating properties and quality, are hardly monitored at all or only inadequately and are not used for process control. As a result, process deviations and variations in coating quality are often detected after coating has been completed, leading to the rejection of entire batches, costly post-treatment, individual sorting, or scrapping, and thus to losses in value creation. Against this background, solutions are required that enable the timely detection of process deviations.

AI-based control through integrated plasma diagnostics

Within the project, two complementary plasma diagnostic methods are synchronized with the coating system, and large volumes of data are evaluated in real time. Building on this, a novel control methodology based on artificial intelligence and machine learning (ML) is being developed. The combination of advanced measurement technologies, data-driven analysis, and intelligent process control represents a genuine innovation and thus closes a critical gap in plasma coating technology.

More efficient processes and new perspectives

The DIGI4PLAS project lays the foundation for the sustainable integration of advanced plasma measurement techniques and pioneering data analysis methods in production processes. This enables significant improvements in process stability, coating quality, and resource efficiency.