The never ending appetite of the mankind to produce more and more competitive products results in continuous development of newer and newer manufacturing processes. One of such a kind, a solid state welding process highly appreciated for joining of a variety of aluminium and copper alloys, is friction stir welding. The process is also an accomplished method for joining dissimilar materials efficiently. The process finds its major application for joining hard-to-weld metals, especially the precipitation hardenable aluminium alloys and is widely adopted by industries for the welding of such aluminium alloys. However, the process has still not found an economical way for welding of steels and hence found limited applications in industries for welding steels. This paper aims at providing a comprehensive review of the work undertaken in the field of friction stir welding and provides an insight into the friction stir welding of aluminium alloys. The article pays critical attention and analytical evaluation of classification of aluminium alloys, friction stir welding process parameters, the mechanical testing and properties of the friction stir welding joints, macrostructure and microstructure evolution during friction stir welding, friction stir welding defects and industrial applications of the process. The friction stir welding process variants are discussed as well. Special accentuation has been given to (i) effect of friction stir welding parameters on the microstructure evolved and thus the ultimate mechanical properties (viz. tensile strength, hardness, fatigue strength, fracture toughness and residual stresses), (ii) the texture formation, microstructure refinement and the role of intermetallics. However, studies related to welding of dissimilar aluminium alloys, temperature, and heat transfer modeling and material flow are out of the scope of this paper. Finally, the directions of future research are examined.

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The present research work explores a pentagonal dense fuzzy set (PDFS) and a novel defuzzification method for the same based on cut. The proposed concept is then applied in the field of inventory management by considering an economic order quantity (EOQ) model. To comprehend the uncertainty associated with the EOQ model, a pentagonal fuzzy number is utilized. Based on PDFS, cloud pentagonal fuzzy number (CPFN) is defined and the model is developed by considering demand as CPFN. The developed models are being tested numerically and graphically to understand the significance of the concept of CPFN. Sensitivity analysis is performed to identify the most critical parameters. A comparative analysis is made to figure out the difference between the models.