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This current research paper measures the performance of Indian private sector banks through various multi-criteria decision-making (MCDM) techniques. To measure the performance of the banks the data about various criteria such as profit after tax, borrowings, advances, adjusted EPS, enterprise value, and NPAs from the Annual reports of the banks were extracted. The MCDM techniques, SDV (standard deviation) CRITIC (CRiteria Importance Through Intercriteria Correlation), ARAS (Additive Ratio Assessment), MOORA (Multi-objective Optimization on the basis of Ratio Analysis) are applied to analyze the data and measure the performance of the banks. In MCDM techniques, different methods provide different weights of the criteria, and also different ranks are obtained by different methods. Sensitivity analysis was carried out by measuring the criteria weights by SDV and CRITIC and the alternatives are ranked using two MCDM techniques, ARAS and MOORA. The results of the study show that among the private banks, HDFC created a benchmark and leading while Yes bank has shown poor performance on the basis of annual reports of 2020.

One of the most widely used 3D printing techniques is fused deposition modeling (FDM) which builds things layer by layer by dispensing molten materials through a heated nozzle. To showcase the flexibility of 3D printing, test samples were made using polylactic acid (PLA). Trial runs with Taguchi’s (L27) orthogonal array were performed. Layer thickness, printing speed, and carbon deposition (C-deposition) were the three input parameters that were improved. This was accomplished by combining principal component analysis (PCA) with multi-objective optimization based on ratio analysis (MOORA) in an integrated approach to multi-criteria optimization. The main goal of this study is to maximize the input parameters for the Industry 4.0 technological production process of embossing components. The MOORA-PCA technique finds the best combinations of process variables; for example, printing at a speed of 75mm/s, layer thickness of 0.1mm, and carbon content of 15mg yield the required results. The results of this study will help production managers and researchers choose the best FDM 3D printing methods for improving mechanical qualities and surface roughness. The economic feasibility of the 3D printing businesses may be strengthened by these research findings, which will benefit customers looking for ecologically friendly items.

This paper represents a multivariate hybrid approach, combining Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) and Principal Component Analysis (PCA) to optimize different correlated responses during Wire Electrical Discharge Machining (WEDM) process of titanium grade 6. The response parameters selected are the average cutting speed, average Kerf width and average surface roughness (Ra). All of them have been studied in terms of pulse-ON time, pulse-OFF time, wire feed and wire tension. As indicated by Taguchi’s signal-to-noise ratio, the optimum process parameters were achieved for the desired average cutting speed, average Kerf width and average surface roughness, respectively. At last, the optimum combination of process parameters was validated by affirmation test which gave considerably improved various quality characteristics. Confirmation test outcome revealed that multivariate hybrid approach MOORA coupled with PCA was a competent strategy to decide available cutting parameters for a desired response quality for WEDM of titanium grade 6.