Low-cycle Fatigue Life Modeling of Similar and Dissimilar Carbon Steel
under Rotary Friction Welding Effect using Adaptive Neuro-Fuzzy
Inference System (ANFIS)
Abstract
Rotary Friction Welding (RFW) is essential in manufacturing automotive
and marine components, yet the low-cycle fatigue life of dissimilar
carbon steel joints (C35 and C45) remains underexplored. This study
investigates the influence of RFW parameters on fatigue life through
experimental and modeling approaches. Axial low-cycle fatigue tests on
base metals and RFW specimens at varying friction pressures show a
direct correlation between friction pressure and fatigue strength
coefficient. The fatigue life was modeled using the Coffin-Manson
equation and refined with an Adaptive Neuro-Fuzzy Inference System
(ANFIS) for enhanced prediction accuracy. Results demonstrated that
higher friction pressure improves fatigue life and weld strength. This
research provides insights into optimizing RFW parameters for better
fatigue performance of carbon steel joints. The integration of
empirical, experimental and ANFIS-based modeling offers practical
guidelines for selecting welding conditions, improving durability and
reducing fatigue testing costs in industrial applications.