The study concerns the coating process of metal substrates in an electrostatic fluidized bed (EFB).
This eco-friendly process is profitably used to coat components of particularly complex shapes. Although this technology is widely spread in several industrial domains, the implementation of appropriate process control procedures is still object of investigation.
A model was generated from experimental data with the aim of predicting, for any set of process parameters, the resulting coating thickness of the sample. With a design of experiment (DOE) approach, the experimental investigation, that is the base for the model, quantifies the coating thickness as a function of the main process parameters namely coating time, applied voltage, and gas flow rate fed into the fluidized bed.
This study addresses the effect of the inherent uncertainties on the predicted coating thickness caused by the approximation in the model parameters. In particular, a fuzzy-logic based approach is used to describe the model uncertainties and the transformation method is used to propagate their effect on the thickness. The fuzzy results are then compared with the data produced by the experimentation leading to the evaluation of the membership level of the dataset to the uncertain model.