Making decisions and deducing control actions in manufacturing environments requires considering many uncertainties. The ability of fuzzy logic to incorporate imperfect information into a decision model has made it suitable for the optimization of both productivity and final quality. In laser surface texturing for wettability control, in fact, these aspects are governed by a complex interaction of many process parameters, ranging from those connected with the laser source to those concerning the properties of the processed material. The proposed fuzzy-based decision approach overcomes this difficulty by taking into account both the random error, associated with the process variability, and the systematic error, due to the modelling assumptions, and propagating such sources of uncertainties at the input level to the output one. In this work, the laser surface texturing was carried out with a nanosecond-pulsed laser on the surfaces of AISI 304 samples, changing the laser scanning speed, the hatch distance, the number of repetitions, and the scanning pattern. A significant change of the contact angle in the range 24-121° is observed due to the produced textures. The fuzzy maps highlight the inherent uncertainty due to both the laser texturing process and the developed model.
Keywords: fuzzy logic; genetic algorithms; laser texturing; soft computing; wettability..