(untitled) (International Journal of Latest Technology in Engineering Management & Applied Science, 2026)
Friction Stir Welding (FSW) is a solid-state joining technique renowned for its ability to produce high-quality welds in aluminum and other non-ferrous metals. A critical parameter influencing weld integrity is the tool tilt angle, which, if improperly set, can lead to defects such as tunnel voids, surface irregularities, or poor material mixing. This study presents a fuzzy logic-based control system for real-time adjustment of the tool tilt angle during FSW. The proposed system utilizes inputs such as torque, temperature, and plunge depth deviation to infer optimal tilt corrections using a Mamdani-type fuzzy inference system. Triangular membership functions and an expert-defined rule base were implemented in MATLAB to simulate adaptive tilt adjustments. Simulation results showed that for a torque input of 10 Nm, a temperature of 45 °C, and a plunge deviation of 0.5 mm, the system produced a tilt adjustment value of 0.224°, as calculated through centroid defuzzification. Surface plots confirmed that the controller responds smoothly to varying conditions, with tilt adjustments ranging from -0.4° to +0.5° based on combined sensor inputs. The proposed system offers a robust and flexible solution suitable for integration into CNC-based FSW platforms for improved automation and weld quality.