Research associate

Research Group:

Industrial Printing

Office hours:

Monday – Friday

In conventional printing processes such as offset printing, the printing process must first be brought to a steady and reliable operation in order to be able to achieve high-quality printing results. Even with modern printing machines, the appropriate adjustment of the process parameters remains partly manual and requires a high level of professional experience.

The goal of my research is to develop, test and validate a data-driven model incorporating machine learning in order to enable intelligent adjustment of process parameters during the printing process. The focus is on identifying the relevant and dominant process parameters, carrying out measurement campaigns on different printing machines and developing a data-driven model including the development of a demonstrator. Since simple metrological approaches have so far failed to deliver satisfactory results, a new approach is to be taken by means of sensor data fusion.