IIARD International Institute of Academic Research and Development

International Journal of Engineering and Modern Technology (IJEMT )

E-ISSN 2504-8848
P-ISSN 2695-2149
VOL. 8 NO. 5 2022
DOI: https://doi.org/10.56201/ijemt.v8.no5.2022.pg13.22

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Grey Relational Analysis-based Interactions of Machining Parameters for Optimal Process Response: An Experimental Initiative

S. L. Bani *, B. Nkoi , H. U. Nwosu

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Abstract

This study, investigated the optimal combining of tool nose radius and cutting variables for the overall performance for both AISI 4140 steel and IS-2062 steel. The both materials were machined on a centre lathe and measurements were taken. The data collected was analysed through grey relational analysis. Results showed that grey relational optimal interactions of machining parameters for the overall performance were: N R (0.35mm), U o (0.5mm), V w (65m/min), R f (0.2mm/rev) for both materials. Also, grey relational grade improved by 1.2767 (24.69%) for the expected optimal design for AISI-4140 steel, and improved by 1.7417 (33.68%) for the expected optimal design for IS-2062 steel. The expected responses were: cutting power 11.157 kW, specific metal removal rate 9.710 mm3/min.kW, cutting force 173.110 N, thrust force 77.207 N, shear force 124.838 N, surface roughness 5.00 , and Shear work 7945.9kNm/min for AISI-4140 steel; and cutting power 5.544 kW, specific metal removal rate 19.541 mm3/min.kW, cutting force 86.074 N, thrust force 39.440 N, shear force 65.688 N, surface roughness 6.165 , and shear work 4158.67 KNm/min for IS-2062 steel. Grey relational analysis reduced the factors affecting on the dependent variables to feed rate and depth of cut.

keywords:

Grey Relational Analysis, Shear Force, Shear Work, Optimization, Cutting Power

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