Data mining techniques for quality improvement of electron beam welding process

Abstract

Besides the fulfilment of the technological requirements for the geometry of the obtained welded joints by electron beam welding, there is a necessity to avoid the conditions, which more probably will lead to defect appearance. It is assumed that the appearance of defects is more probable under some regime conditions. For the modelling of the dependence of bivariate quality characteristics (such as the defect appearance) on the process parameters two different modelling approaches are applied and compared – logistic regression and neural networks. The implemented model-based approaches are compared and applied for the prediction of the defect appearance, depending on the variation of the electron beam process parameters.