Publication:
Optimization and comparison of machining characteristics of SKD61 steel in powder-mixed EDM process by TOPSIS and desirability approach

cris.author.scopus-author-id 57211342352
cris.author.scopus-author-id 57210826052
cris.author.scopus-author-id 57428935900
cris.author.scopus-author-id 56959937800
cris.author.scopus-author-id 58727839400
cris.author.scopus-author-id 57226681885
cris.author.scopus-author-id 58726637800
dc.contributor.author Le V.T.
dc.contributor.author Hoang L.
dc.contributor.author Ghazali M.F.
dc.contributor.author Le V.T.
dc.contributor.author Do M.T.
dc.contributor.author Nguyen T.T.
dc.contributor.author Vu T.S.
dc.date.accessioned 2024-10-01T06:38:03Z
dc.date.available 2024-10-01T06:38:03Z
dc.date.issued 2024-01-01
dc.description.abstract In this paper, tungsten carbide powder adding the dielectric liquid during electro-discharge machining (EDM) process for processing SKD61 steel was explored. Firstly, the influence of main process variables, comprising peak current (Ip), pulse on time (T on), and amount of powder (Ap) on material removal rate (MRR), tool wear rate (TWR), and surface roughness (Ra) was explored. Secondly, an optimal combination of these process variables is sought to enhance the quality of surfaces, MRR, and reduce TWR. A series of 15 experiments of the Box-Behnken design was performed. Subsequently, adequate mathematical models for MRR, TWR, and Ra were established, with the application of analysis of variance (ANOVA) to evaluate the adequacy of these models. Finally, Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and desirability approach (DA) were adopted for the multi-attribute optimization. Besides, Non-Dominated Sorting Genetic Algorithm II (NSGA II)-evaluation by an area-based method of ranking (EAMR) was also conducted and compared with both DA and TOPSIS for the most appropriate choice. The outcomes indicated that Ip demonstrates the strongest influence on Ra, MRR, and TWR, followed by T on and Ap for MRR, while the proceeding effect is Ap and T on for TWR and Ra. In comparison with TOPSIS, DA provides the best solution with a decline of 41.5% in TWR and an increment of 22.7% in MRR, while TOPSIS contributes the best solution with a drop of 13.89% in Ra when compared with DA. In addition, TOPSIS provides better surface quality than DA.
dc.identifier.doi 10.1007/s00170-023-12680-8
dc.identifier.scopus 2-s2.0-85178109064
dc.identifier.uri https://hdl.handle.net/20.500.14170/7285
dc.relation.funding National Foundation for Science and Technology Development
dc.relation.grantno 107.99–2021.29
dc.relation.ispartof International Journal of Advanced Manufacturing Technology
dc.relation.ispartofseries International Journal of Advanced Manufacturing Technology
dc.relation.issn 02683768
dc.subject EDM | MRR | Multi-response optimization | Surface roughness | Tungsten carbide | TWR
dc.title Optimization and comparison of machining characteristics of SKD61 steel in powder-mixed EDM process by TOPSIS and desirability approach
dc.type Journal
dspace.entity.type Publication
oaire.citation.endPage 424
oaire.citation.issue 1-2
oaire.citation.startPage 403
oaire.citation.volume 130
oairecerif.affiliation.orgunit Le Quy Don Technical University
oairecerif.affiliation.orgunit Hanoi University of Science and Technology
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
oairecerif.affiliation.orgunit Le Quy Don Technical University
oairecerif.affiliation.orgunit Le Quy Don Technical University
oairecerif.affiliation.orgunit Le Quy Don Technical University
oairecerif.affiliation.orgunit Military Weapon Institute
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person.identifier.scopus-author-id 57211342352
person.identifier.scopus-author-id 57210826052
person.identifier.scopus-author-id 57428935900
person.identifier.scopus-author-id 56959937800
person.identifier.scopus-author-id 58727839400
person.identifier.scopus-author-id 57226681885
person.identifier.scopus-author-id 58726637800
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