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Article type: Research Article
Authors: Mystica, A.a | Senthil kumar, V.S.a; * | Sakthi abirami, B.b
Affiliations: [a] Department of Mechanical Engineering, CEG, Anna University, Tamilnadu, India | [b] Amrita School of Engineering, Amrita Vishwa Vidhyapeedham, Tamilnadu, India
Correspondence: [*] Corresponding author. Professor, Department of Mechanical Engineering, CEG, Anna University, Tamilnadu, India. E-mail: [email protected].
Abstract: AA2014 is an Al-Cu alloy friction stir welded under different combinations of rotational speed (800, 1000 and 1200 rpm) and transverse speed (44, 60, 72 mm/min) under minimum quantity lubrication condition with graphene nanofluid as coolant. Design of experiments is performed using Taguchi L9 orthogonal array. Analysis of variance technique is adapted to find the most influencing input parameter (rotational speed, transverse speed) of each output response (ultimate tensile strength, % elongation, microhardness and grain size). Regression and fuzzy logic based models are developed to predict the output responses. The reliability of the predicted results is tested by calculating the correlation coefficient. The predicted results from regression and fuzzy logic are then compared with the experimental results. The results of trend analysis exhibit the substantial influence of both the input parameters on the output responses. The results from ANOVA reveals that the rotational speed highly influences ultimate tensile strength and grain size while transverse speed majorly influences microhardness. The error in prediction using fuzzy model is observed to be significantly limited with correlation coefficients in the range of 0.70–0.96. The developed models are observed to be highly efficient and therefore can be used for prediction in any uncertain engineering applications.
Keywords: Friction stir welding, minimum quantity lubrication, graphene nanofluid, regression modelling, fuzzy logic
DOI: 10.3233/JIFS-213032
Journal: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 2375-2390, 2022
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