2023
DOI: 10.1088/2631-8695/acb6d1
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Analysis of tensile strength on friction stir welded Al 6061 composite reinforced with B4C and Cr2O3 using RSM and ANN

Abstract: Aluminum (Al) alloys are reinforced with carbides and oxides to enhance their properties. Al composites are developed to meet current automotive, shipbuilding, and aviation requirements. In the current study, aluminum 6061 is reinforced with B4C and Cr2O3 separately to fabricate Al6061 + B4C and Al 6061+Cr2O3 aluminum metal matrix composites (Al MMC). The Al composites were fabricated by stir casting with a wt % in steps of 2%, 4%, and 6%. Joining of Al MMC is essential to develop valuable components. The deve… Show more

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Cited by 7 publications
(11 citation statements)
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“…From this observation it is quite clear that the values predicted using ANN model are far more accurate than those predicted by RSM. The observation is well in line those reported by Tyagi et al [29] and Alam et al [31] on better predictive capability of ANN on wear behaviour of Al composites. Although under certain conditions RSM model did showed better predictive capability when compared with ANN model [27] however in most cases the ANN showed high reliability.…”
Section: Predictive Capacity Of Rsm and Annsupporting
confidence: 92%
See 1 more Smart Citation
“…From this observation it is quite clear that the values predicted using ANN model are far more accurate than those predicted by RSM. The observation is well in line those reported by Tyagi et al [29] and Alam et al [31] on better predictive capability of ANN on wear behaviour of Al composites. Although under certain conditions RSM model did showed better predictive capability when compared with ANN model [27] however in most cases the ANN showed high reliability.…”
Section: Predictive Capacity Of Rsm and Annsupporting
confidence: 92%
“…In the last decade lot of effort has been devoted towards using optimization tool like Taguchi's experimental design method, response surface methodology (RSM) and soft computing tool such as artificial neural network (ANN) for prediction of tribological properties of Al nanocomposites [26][27][28][29]. Although these tools were extensively used for prediction of tool wear and surface finish of metallic or composite materials subjected to machining but extending them to optimization of wear parameters of nanocomposites is relatively new.…”
Section: Introductionmentioning
confidence: 99%
“…A widely employed 6xxx series aluminium alloy AA6061 [24,25] with a density of 2.7 g cm −13 was used as the matrix in the study. The spectroscopic analysis of the alloy revealed the presence of 0.73, and 0.95 weight percentages (wt%) of Si, and Mg respectively, which are the major alloying elements and are within the permissible limits according to the standard AA6061.…”
Section: Methodsmentioning
confidence: 99%
“…TOPSIS approach was used to optimize hardness and impact energy simultaneously (Suganeswaran et al , 2023). Uday et al used artificial neural network in conjugation with RSM for getting superlative output (Uday and Rajamurugan 2023a, 2023b).…”
Section: Introductionmentioning
confidence: 99%