Technical gazette, Vol. 30 No. 1, 2023.
Original scientific paper
https://doi.org/10.17559/TV-20220222080715
Multi-Response Optimization in MQLC Machining Process of Steel St50-2 Using Grey-Fuzzy Technique
Mario Dragičević
orcid.org/0000-0001-5566-8145
Edin Begović
; University of Zenica, Faculty of Mechanical Engineering, Fakultetska 1, Zenica 72000, Bosnia and Hercegovina
Sabahudin Ekinović
; University of Zenica, Faculty of Mechanical Engineering, Fakultetska 1, Zenica 72000, Bosnia and Hercegovina
Ivan Peko
; University of Split, Faculty of Science, Ruđera Boškovića 33, 21000 Split
Abstract
In this paper MQLC turning process of steel St 50-2 is presented. Experimentations were performed using Taguchi L9 orthogonal array by varying two process parameters such as oil and water quantity while other parameters such as cutting speed, feed rate and depth of cut were kept constant. Process responses that were analyzed in this paper are surface roughness Ra and resultant cutting force Frez. In order to quantify significance of each process parameter on analyzed response ANOVA was conducted. Fuzzy logic modelling technique was used to describe the effects of process parameters and to create response surface plots. Finally, in order to find out process parameters values that lead simultaneously to optimal surface roughness and resultant cutting force, multi-objective optimization of process responses was conducted by using grey relational analysis (GRA) combined with fuzzy logic technique.
Keywords
grey relational analysis; fuzzy logic; MQLC system; multi-response optimization; steel
Hrčak ID:
288424
URI
Publication date:
15.12.2022.
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