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Straight turning optimization of low alloy steel using MCDM methods coupled with Taguchi approach

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Abstract

Modern manufacturing’s objective is to guarantee quality while lowering production costs and increasing productivity. In this context, the selection of cutting materials is important in increasing productivity due to their wide range of applications. In this paper, when machining AISI 4140 alloy steel, an experimental study is presented to find the cutting conditions that result in minimum Ra, Vb, and maximum MRR values. Different optimization methods are used, namely, Taguchi, grey relational analysis (GRA), technique by order of preference by similarity to ideal solution (TOPSIS), and multi-objective optimization ratio analysis (MOORA). Taguchi’s L16 design was used to arrange 16 experiments. Cutting speed (Vc), feed rate (f), and depth of cut (ap) were the input parameters, with four levels for each cutting parameter. The feed rate and cutting speed had the greatest effect on Ra and Vb, according to an ANOVA analysis of the experimental results. MRR was significantly affected by the depth of cut and feed rate. To achieve the minimum surface roughness, flank wear, and maximum material removal rate, the cutting speed, feed rate, and depth of cut were required to be 250 m/min, 0.11 mm/rev, and 1.4 mm, respectively, according to the optimization results.

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Acknowledgements

The authors would like to thank all members of the LMS laboratory for their support.

Funding

The work is funded by (LMS) Laboratory of the 8 May 1945 Guelma University, Algeria, and received funding from the General Directorate of Scientific Research and Technological Development (DGRSDT) under the PRFU research project A11N01UN240120220002.

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Correspondence to Salah Hadjela.

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Hadjela, S., Belhadi, S., Ouelaa, N. et al. Straight turning optimization of low alloy steel using MCDM methods coupled with Taguchi approach. Int J Adv Manuf Technol 124, 1607–1621 (2023). https://doi.org/10.1007/s00170-022-10584-7

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