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      A grey-fuzzy based multi-response optimisation study on the friction and wear characteristics of titanium diboride reinforced aluminium matrix composite

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          Abstract

          Aluminium matrix composites are nowadays used globally as a substitute for other cast alloys because of their augmented properties. The present experiment deals with the fabrication and characterisation of tribological behaviour of titanium diboride reinforced aluminium matrix composite on a pin-on-disc tribotester under dry sliding condition. In this work, an attempt has been made to minimise the friction and wear characteristics of Al2024-TiB 2 composite, by optimising the tribological parameters viz. applied load, sliding speed and sliding distance using grey-fuzzy approach. The tests are carried out based on Taguchi’s L25 orthogonal array. Grey-fuzzy analysis is used for converting the multi-objective optimisation problem into a single-objective optimisation. Based on the grey-fuzzy analysis, the optimal combination of tribological parameters is L1S4D2 (10N load, 2.0 m/s sliding speed and 1000 m sliding distance). The optimal combination of parameters has also been validated with a confirmatory experiment. Analysis of variance (ANOVA) for grey fuzzy grade shows that sliding distance is the most significant parameter affecting tribological performance. SEM analysis of the worn surfaces revealed that, increase in sliding distance results in wear transition from mild to severe. The proposed grey-fuzzy method is found to be successful in solving multi-response tribological problems.

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          Most cited references45

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          Fuzzy sets

          L.A. Zadeh (1965)
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            Tensile and fracture behavior of nano/micro TiB2 particle reinforced casting A356 aluminum alloy composites

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              A hybrid ANN-Fuzzy approach for optimization of engine operating parameters of a CI engine fueled with diesel-palm biodiesel-ethanol blend

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                Author and article information

                Contributors
                Journal
                Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture
                Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture
                SAGE Publications
                0954-4054
                2041-2975
                December 2023
                January 12 2023
                December 2023
                : 237
                : 14
                : 2227-2239
                Affiliations
                [1 ]Mechanical Engineering Department, NIT Agartala, Agartala, Tripura, India
                [2 ]Mechanical Engineering Department, Dream Institute of Technology, Kolkata, India
                Article
                10.1177/09544054221147973
                e6fd3dd2-86a5-4085-a457-7fff7dca00ee
                © 2023

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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