Introduction of a day effect estimator in order toimprove the prediction of particle properties in anHVOF spraying jet

Thermal spraying processes are influenced by a wide variety of controllable and non-controllable factors. Due to random disturbance variables, spraying results may be extremely different depending on the day. With the aid of modern process diagnostics, it can be shown that, with the same process parameters, the properties of the particles in flight change on different days. Especially the particle temperature is affected by such fluctuations. Therefore, ensuring the reproducibility of spraying processes may already start on the level of the particle properties. The solution approach presented here compensates for the process fluctuations by extending statistical forecast models by an additive day-dependent effect estimator. This is established by taking just a few initialisation measurements at the beginning of a measuring day and the process parameters are adjusted according to the models in order to eliminate the day effect. This served to substantially improve the prediction quality of the model.