This paper describes research conducted on the automation for a UV-laser-based surface pre-treatment of fibre-reinforced composites in order to improve adhesive bonding conditions. In a preceding process step, a laser-line-triangulation-system gathered inline information on a composite part’s surface like topology and location of surface contaminants. This data is the basis for an automation of the laser-based surface treatment. The gathered data describes the position of bonding areas and surface contaminants and is converted into relative coordinates of the laser’s scanning field. During the following laser process, the bonding area is ablated to improve adhesive bonding conditions. The process is monitored online by a broad bandwidth spectrometer covering the range of λ = 200nm - 1,100nm to detect changes in surface composition. If the spectrometer detects signals related to specific surface contaminants during the laser process, the position of the contamination is logged. In this case, only the areas that showed traces of surface contaminations are laser treated again until the spectrometer stops detecting the contaminant signature. This work presents results of two series of experiments. During the first series of experiments, the spectrometer monitored a UV-laser process on a carbon fibre reinforced epoxy. The laser processing was performed on a clean and contaminated surface respectively. An industry standard release agent contaminated the plastic surface. The spectrometer detected differences between the clean and contaminated surface that will be used for an automatic process control. In a second series of experiments, the authors performed a processing parameter analysis in order to identify a potential process window for laser-based surface pre-treatment for glass-fibre reinforced polyamide 6. Contact angle analysis, surface roughness measurements, peel-strength and shear strength tests were performed. The results show that an inline controlled laser process is robustly able to pre-treat composite surfaces based on spectrometric measurements.