Professor of School of Engineering, Design and Built Environment, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.
2024-02-24
2024-01-04
2023-11-02
Abstract—The turning process is considered to be one of the most important machining processes. The various combinations of the input parameters can indeed determine the fate of the quality of the produced parts. This study aims to investigate the effect of various combinations of the input parameters on the surface roughness and the force required in order to elicit the optimal set. An L18 orthogonal array has been constructed using the JMP software for four input variables (i.e. the use of lubricant, cutting speed, depth of cut, and feed rate). Grey relational analysis has been utilized to identify the optimal set of the investigated inputs, which leads to the optimal machining characteristics (i.e. surface roughness and cutting force). Index Terms—grey relational analysis, Taguchi, turning process, surface roughness, cutting force Cite: Lamees Al-Durgham, Wafa’ H. AlAlaween, and Nibal T. Albashabsheh, "Optimizing the Turning Operation via Using the Grey Relational Grade," International Journal of Mechanical Engineering and Robotics Research, Vol. 11, No. 6, pp. 452-459, June 2022. DOI: 10.18178/ijmerr.11.6.452-459 Copyright © 2022 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.
