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 (T_on), pulse-off time (T_off), and current—were chosen, each having three levels to monitor the process response in terms of cutting speed (V_C), 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 T_on = 40 µs, T_off = 15 µs, and current = 2A.

Machining of Titanium alloys (Ti6Al4V) becomes more vital due to its essential role in biomedical, aerospace, and many other industries owing to the enhanced engineering properties. In the current study, a Box–Behnken design of the response surface methodology (RSM) was used to investigate the performance of the abrasive water jet machining (AWJM) of Ti6Al4V. For process parameter optimization, a systematic strategy combining RSM and a heat-transfer search (HTS) algorithm was investigated. The nozzle traverse speed (T_v), abrasive mass flow rate (A_f), and stand-off distance (S_d) were selected as AWJM variables, whereas the material removal rate (MRR), surface roughness (SR), and kerf taper angle (θ) were considered as output responses. Statistical models were developed for the response, and Analysis of variance (ANOVA) was executed for determining the robustness of responses. The single objective optimization result yielded a maximum MRR of 0.2304 g/min (at T_v of 250 mm/min, A_f of 500 g/min, and S_d of 1.5 mm), a minimum SR of 2.99 µm, and a minimum θ of 1.72 (both responses at T_v of 150 mm/min, A_f of 500 g/min, and S_d of 1.5 mm). A multi-objective HTS algorithm was implemented, and Pareto optimal points were produced. 3D and 2D plots were plotted using Pareto optimal points, which highlighted the non-dominant feasible solutions. The effectiveness of the suggested model was proved in predicting and optimizing the AWJM variables. The surface morphology of the machined surfaces was investigated using the scanning electron microscope. The confirmation test was performed using optimized cutting parameters to validate the results.

The feasibility of producing welding joints between 6061-T6 aluminum and pure copper sheets of 6 mm thickness by conventional friction stir welding (CFSW) and bobbin tool friction stir welding (BTFSW) by using a slot-groove configuration at the joining surface was investigated. The microstructure of the welded samples was examined by using an optical microscope and X-ray diffraction. Furthermore, the mechanical properties of the weld samples are compared based on the results of the tensile test, hardness measurement, and fractography test. The slot-groove configuration resulted in the presence of a bulk-sized Al block on the Cu side. The microscopic observations revealed the dispersion of fine Cu particles in the stir zone. The presence of intermetallic compounds (IMCs) CuAl₂, which are hard and brittle, lowered the strength of the weld joints. The strength of the weld joints produced with BTFSW was superior to that of the C-FSW. The maximum hardness values of 214 HV and 211 HV are reported at the stir zone for BTFSW and CFSW, respectively. The fracture location of all the joints was at the intersection of the stir zone and the thermomechanically affected zone was on the Cu side.

There are several environmental and energy concerns of using gasoline motorcycles which has led to the rapid development in the electric motorcycle industry. Electric motorcycles provide several decisive features along with tremendous energy efficiency which overcomes several environmental pollution problems created due to the existing gasoline motorcycles. This paper presents CRITIC-COPRAS and CRITIC-TOPSIS multi-criteria decision-making techniques for the best selection of electric motorcycles. The notable idea of this approach is to compare both the techniques to find most relevant technique for motorbike selection scenario to help decision makers determine best alternative among a distinct set of available electric motorcycle options in the market.