eprintid: 16708
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/67/08
datestamp: 2023-12-19 03:23:14
lastmod: 2023-12-19 03:23:14
status_changed: 2023-12-19 03:06:45
type: article
metadata_visibility: show
creators_name: Danish, M.
creators_name: Al-Amin, M.
creators_name: Rubaiee, S.
creators_name: Abdul-Rani, A.M.
creators_name: Zohura, F.T.
creators_name: Ahmed, A.
creators_name: Ahmed, R.
creators_name: Yildirim, M.B.
title: Enhanced machining features and multi-objective optimization of CNT mixed-EDM process for processing 316L steel
ispublished: pub
keywords: Aluminum compounds; Analysis of variance (ANOVA); Austenitic stainless steel; Carbon nanotubes; Cutting tools; Industrial research; Morphology; Multiobjective optimization; Scanning electron microscopy; Wear of materials, 316L steel; Electrodischarges; Erosion rates; Material erosion; Multi objective; Multi-objective ant lion optimizer; Optimizers; Process parameters; Tool wear rate; Wear surface, Surface roughness
note: cited By 10
abstract: There is a high roughness and tool wear rate (TER), and a minimal material erosion rate (MER) when 316L steel is machined through conventional or conductive powder mixed electro-discharge (EDM) processes. Since the required machining outputs are primarily dependent on process parameters due to their fluctuating nature during the operation, a thorough study is required. This research intends to investigate the effects of EDM process parameters on the machining outputs. The carbon nanotubes (CNT) are added to the working dielectric to achieve a high MER with a low TER and surface roughness (SR). The machined surface�s morphology and composition are validated using scanning electron microscope (SEM) and electron dispersive X-ray (EDX). Taguchi�s design has been employed to conduct the EDM process parametric optimization obtaining the smallest TER and SR of 0.34 mg/min and 1.55 µm, respectively. The greatest MER of 39.76 mg/min, which is considered for the machining efficacy, is obtained. The most relevant factor for MER, TER, and SR is current intensity, followed by CNT quantity, according to analysis of variance (ANOVA). The estimated errors of the predicted solution sets using the multi-objective ant lion optimizer (MOALO) are less than 10, which confirm a high prediction of them. Findings of this research will result in an effective manufacturing process for fabricating the devices made of 316L steel for biomedical and oil and gas applications. © 2022, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.
date: 2022
publisher: Springer Science and Business Media Deutschland GmbH
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127594083&doi=10.1007%2fs00170-022-09157-5&partnerID=40&md5=b49801eab33ca7a85d0712205eb6b687
id_number: 10.1007/s00170-022-09157-5
full_text_status: none
publication: International Journal of Advanced Manufacturing Technology
volume: 120
number: 9-10
pagerange: 6125-6141
refereed: TRUE
issn: 02683768
citation:   Danish, M. and Al-Amin, M. and Rubaiee, S. and Abdul-Rani, A.M. and Zohura, F.T. and Ahmed, A. and Ahmed, R. and Yildirim, M.B.  (2022) Enhanced machining features and multi-objective optimization of CNT mixed-EDM process for processing 316L steel.  International Journal of Advanced Manufacturing Technology, 120 (9-10).  pp. 6125-6141.  ISSN 02683768