Friction stir welding is a solid-state welding technique for joining similar and dissimilar material. Bobbin tool friction stir welding (BTFSW) is a variant of the conventional friction stir welding process (CFSW). Compared with conventional FSW, BTFSW eliminates all limitations of CFSW using a two shoulders configuration. Now, the need has arisen to review the work done on BTFSW to provide broader aspects of the technique to researchers. This paper aims at providing comprehensive insight on the BTFSW. The paper pays critical attention to tool material selection, design features of shoulder and pin surfaces, microstructure evolution, mechanical characterisation, derivatives, and challenges in this technique. Further, welding defects and future scope of BTFSW are also addressed in this paper.

Titanium and its alloys exhibit numerous uses in aerospace, automobile, biomedical and marine industries because of their enhanced mechanical properties. However, the machinability of titanium alloys can be cumbersome due to their lower density, high hardness, low thermal conductivity, and low elastic modulus. The wire electrical discharge machining (WEDM) process is an effective choice for machining titanium and its alloys due to its unique machining characteristics. The present work proposes multi-objective optimization of WEDM on Ti6Al4V alloy using a fuzzy integrated multi-criteria decision-making (MCDM) approach. The use of MCDM has become an active area of research due to its proven ability to solve complex problems. The novelty of the present work is to use integrated fuzzy analytic hierarchy process (AHP) and fuzzy technique for order preference by similarity to ideal situation (TOPSIS) to optimize the WEDM process. The experiments were systematically conducted adapting the face-centered central composite design approach of response surface methodology. Three independent factors—pulse-on time (Ton), pulse-off time (Toff), and current—were chosen, each having three levels to monitor the process response in terms of cutting speed (VC), material removal rate (MRR), and surface roughness (SR). To assess the relevance and significance of the models, an analysis of variance was carried out. The optimal process parameters after integrating fuzzy AHP coupled with fuzzy TOPSIS approach found were Ton = 40 µs, Toff = 15 µs, and current = 2A.

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