Aldaş, KemalÖzkul, İskenderAkkurt, Adnan13.07.20192019-07-1613.07.20192019-07-1620141310-4772https://hdl.handle.net/20.500.12451/2592In this study, adaptive neuro-fuzzy inference system (ANFIS) modelling was used for estimation surface roughness based on experimental study of after processing with wire electrical discharge machining (WEDM) in Dievar hot work tool steel. Feed rate (fr), current (C), and pulse on time (POn) as independent variables were carried out in experimental study and modelling. Two different membership functions and different estimation types were conducted. The model based plots showed the machining parameters effects on the surface roughness and Gaussian membership function type performed better results than Bell-shaped membership function.eninfo:eu-repo/semantics/closedAccessANFISRoughnessTool steelWEDMArticle204548558Q4N/A