Fuzzy assisted grey Taguchi approach for optimisation of multiple weld quality properties in friction stir welding process

Abstract

Friction stir welding (FSW) is gaining its popularity for a wide range of high strength/weight ratio materials such as aluminium, magnesium, composites and plastics. With the projected prevalent application of FSW, it is necessary to identify the optimal welding condition with a small number of experiments for effective product quality and productivity. In this study, a fuzzy assisted grey Taguchi method is proposed for optimising the FSW process parameters with multiple weld quality characteristics. The fuzzy inference system was adapted to convert the multiresponse optimisation problem into an equivalent single objective optimisation problem, which was solved by the Taguchi approach. Eight input process parameters have been varied to observe their effects on output responses, namely, ultimate tensile strength, yield strength, % elongation, weld bead thickness and nugget zone hardness. Confirmation test showed that the proposed approach can efficiently be used for the optimisation of multiple weld quality properties in FSW process.