Effects of plasma arc cutting process parameters on the cutting speed optimization based on the required cut quality

A number of real time problems in immediate production implied the investigation of various methods for adequate cutting speed selection based on the pre-defined cut quality. In this paper, cutting speed was optimized by the development of regression and artificial neural network models, were the impact of kerf width, cutting current and material thickness was monitored. The experimental research provided sufficient data for the models' development and their validation. The effects of models application were evaluated by visual data inspection and statistical data analysis. This study revealed the pace of cutting speed changes based on the selected input model parameters, which allows adapting cutting conditions to the product requirements, either in functional, quality or cost terms.(c) 2022 CIRP.