Machining of the nickel-based alloy is very demanding due to its extreme mechanical properties, for example, higher fatigue strength, better corrosion and creep resistance feature, substantial work hardening capability, and appreciable tensile and shear strength. Owing to these properties, the selection of machining parameters is a major challenge for modern machining industries. Therefore, the present experimental work is carried out to select the best parametric combination of the wire electrical discharge machining (WEDM) machine for reducing machining cost and human effort. The Trapezoidal Interval Type-2 fuzzy number (T2FS) integrated Analytical Hierarchy Process (AHP)-based Additive Ratio Assessment (ARAS) method is used for selecting the best WEDM process parameters of Inconel-800 superalloy. Finally, the results were compared with some existing multi-criteria decision-making methods to confirm the validity of the adopted method. The comparison shows that Type-2 Fuzzy AHP-ARAS synergy can help to formulate the problem and facilitate the assessment and ranking of WEDM process parameters when multiple criteria are jointly considered.

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The paper focuses on developing a novel decision-making model, to select the best welding parameters for friction stir welding of dissimilar aluminium to copper plates. A set of 21 experiments are carried out based on a d-optimal design matrix. Apart from considering the rotational speed and traverse speed as input variables, the position of aluminium and copper either in the advancing or retreating side is also considered as an input variable. On the successful fabrication of joints, the ultimate tensile strength, elongation, hardness and impact energy are estimated experimentally which are considered as performance parameters. The proposed decision-making process is categorized under multi-criteria decision-making (MCDM) methods. In the first phase, the novel MCDM model is applied to select the best welding parameters. The concept of the model is to minimize the risk of not attaining the global best result. The results obtained by the MCDM method is justified by carrying out a sensitivity analysis and finally validated with the results obtained from the fuzzy logic decision-making approach. The second phase is related to the computation of optimized values for the joining process that reports the development of a mathematical model by response surface methodology to predict different performance parameters. This is followed by conducting a trade-off analysis by developing a multi-objective response surface methodology (MORSM) that computes the optimal welding parameters. Finally, a confirmatory test is carried out for validation of the proposed MORSM model.

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