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Multi-Response Optimization of Electrical Discharge Machining Using the Desirability Function †
Electrical discharge machining (EDM) is a modern technology that is widely used in the production of difficult to cut conductive materials. The basic problem of EDM is the stochastic nature of electrical discharges. The optimal selection of machining parameters to achieve micron surface roughness an...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6356736/ https://www.ncbi.nlm.nih.gov/pubmed/30669518 http://dx.doi.org/10.3390/mi10010072 |
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author | Świercz, Rafał Oniszczuk-Świercz, Dorota Chmielewski, Tomasz |
author_facet | Świercz, Rafał Oniszczuk-Świercz, Dorota Chmielewski, Tomasz |
author_sort | Świercz, Rafał |
collection | PubMed |
description | Electrical discharge machining (EDM) is a modern technology that is widely used in the production of difficult to cut conductive materials. The basic problem of EDM is the stochastic nature of electrical discharges. The optimal selection of machining parameters to achieve micron surface roughness and the recast layer with the maximal possible value of the material removal rate (MRR) is quite challenging. In this paper, we performed an analytical and experimental investigation of the influence of the EDM parameters: Surface integrity and MRR. Response surface methodology (RSM) was used to build empirical models on the influence of the discharge current I, pulse time t(on,) and the time interval t(off), on the surface roughness (Sa), the thickness of the white layer (WL), and the MRR, during the machining of tool steel 55NiCrMoV7. The surface and subsurface integrity were evaluated using an optical microscope and a scanning profilometer. Analysis of variance (ANOVA) was used to establish the statistical significance parameters. The calculated contribution indicated that the discharge current had the most influence (over the 50%) on the Sa, WL, and MRR, followed by the discharge time. The multi-response optimization was carried out using the desirability function for the three cases of EDM: Finishing, semi-finishing, and roughing. The confirmation test showed that maximal errors between the predicted and the obtained values did not exceed 6%. |
format | Online Article Text |
id | pubmed-6356736 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-63567362019-02-05 Multi-Response Optimization of Electrical Discharge Machining Using the Desirability Function † Świercz, Rafał Oniszczuk-Świercz, Dorota Chmielewski, Tomasz Micromachines (Basel) Article Electrical discharge machining (EDM) is a modern technology that is widely used in the production of difficult to cut conductive materials. The basic problem of EDM is the stochastic nature of electrical discharges. The optimal selection of machining parameters to achieve micron surface roughness and the recast layer with the maximal possible value of the material removal rate (MRR) is quite challenging. In this paper, we performed an analytical and experimental investigation of the influence of the EDM parameters: Surface integrity and MRR. Response surface methodology (RSM) was used to build empirical models on the influence of the discharge current I, pulse time t(on,) and the time interval t(off), on the surface roughness (Sa), the thickness of the white layer (WL), and the MRR, during the machining of tool steel 55NiCrMoV7. The surface and subsurface integrity were evaluated using an optical microscope and a scanning profilometer. Analysis of variance (ANOVA) was used to establish the statistical significance parameters. The calculated contribution indicated that the discharge current had the most influence (over the 50%) on the Sa, WL, and MRR, followed by the discharge time. The multi-response optimization was carried out using the desirability function for the three cases of EDM: Finishing, semi-finishing, and roughing. The confirmation test showed that maximal errors between the predicted and the obtained values did not exceed 6%. MDPI 2019-01-20 /pmc/articles/PMC6356736/ /pubmed/30669518 http://dx.doi.org/10.3390/mi10010072 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Świercz, Rafał Oniszczuk-Świercz, Dorota Chmielewski, Tomasz Multi-Response Optimization of Electrical Discharge Machining Using the Desirability Function † |
title | Multi-Response Optimization of Electrical Discharge Machining Using the Desirability Function † |
title_full | Multi-Response Optimization of Electrical Discharge Machining Using the Desirability Function † |
title_fullStr | Multi-Response Optimization of Electrical Discharge Machining Using the Desirability Function † |
title_full_unstemmed | Multi-Response Optimization of Electrical Discharge Machining Using the Desirability Function † |
title_short | Multi-Response Optimization of Electrical Discharge Machining Using the Desirability Function † |
title_sort | multi-response optimization of electrical discharge machining using the desirability function † |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6356736/ https://www.ncbi.nlm.nih.gov/pubmed/30669518 http://dx.doi.org/10.3390/mi10010072 |
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