Abstract
Metal matrix composites reinforced with low-cost industrial waste materials such as cupola slag are high in demand due to their low cost and tailored properties. In this experimental investigation, fabrication of cupola slag-reinforced aluminum matrix composite has been performed using a stir casting route. Cast composites need to be machined for various applications. The study of machinability in terms of material removal rate (MRR) in dry turning of cupola slag-reinforced aluminum metal matrix composites has been performed. Analysis and prediction of MRR induced in the machining have been the objective of this work. Spindle speed, feed rate and weight percentage of cupola slag are chosen as the process parameters, and their influence over MRR has been analyzed. Experiments have been designed using Taguchi L9 orthogonal array. A predictive model of MRR has been obtained using regression and fuzzy logic. The comparison between regression and fuzzy logic prediction has been done in terms of root mean squared error (RMSE). The fuzzy logic was observed to be more accurate in terms of prediction with an error of 0.81%, whereas the regression model yields an error of 1.10%.
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Acknowledgements
Department of Science & Technology and Biotechnology, Government of West Bengal (Memo No.: 114 (Sanc.)/STBT—11012(16)/16/2021—ST SEC dated 28.04.2022) has been acknowledged by authors for funding this work.
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Chakravarty, S., Haldar, P., Nandi, T., Sutradhar, G. (2023). Fuzzy Logic-Based Model for Predicting Material Removal Rate of Machined Cupola Slag-Reinforced Aluminum Metal Matrix Composite. In: Swain, B.P. (eds) Recent Advances in Materials. ICSTE 2023. Springer Proceedings in Materials, vol 25. Springer, Singapore. https://doi.org/10.1007/978-981-99-3844-5_19
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DOI: https://doi.org/10.1007/978-981-99-3844-5_19
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