Identification and Modeling of Wire Arc Additive Manufacturing under consideration of Interpass Temperature

Wire Arc Additive Manufacturing offers the possibility to use the advantage of additive manufacturing on a larger scale due to high build rates. However, the influence of disturbances and the unknown process behavior hamper wider application. Model building and identification make it possible to increase robustness and repeatability through the use of process control. The identification is done as a SISO model and by means of a neural network, the simulation results are validated with measured output variables. In addition, the influence of the interpass temperatures is considered as well as computational effort and extensibility to several process variables are investigated.