Autonomous, calibration-free online process optimization

• Applicant: Professor Dr. Thorsten Röder
• Subject Area: Chemical and Thermal Process Engineering
• Term: since 2026
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 569114483

Online analytics (based on calibration functions) are the key component in our preliminary research project on autonomous process optimization. Previously determined calibration functions are required to analyze the spectroscopic data. However, the generation of these calibration functions can be very time-consuming, cost- and material-intensive. In particular, this is the case when multivariate calibration, for example partial least squares (also known as Projection on Latent Structures, PLS) regression, is necessary due to non-baseline separated bands, as in near-infrared spectroscopy and UV/Vis spectroscopy. However, our preliminary work has shown that calibration is no longer necessary as Multivariate Curve Resolution (MCR) can be applied. Therefore, our working hypothesis for this Transfer HAW/FH PLUS project is that the combination of autonomous process optimization with the MCR approach offers an adequate method for the development of an efficient, calibration-free and universally applicable process optimization platform.

• DFG Programme: Research Grants (Transfer Project)
• Application Partner: BASF SE