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The Optimal Processing Parameters of Radial Ultrasonic Rolling Electrochemical Micromachining—RSM Approach
Radial ultrasonic rolling electrochemical micromachining (RUR-EMM) is a new method of electrochemical machining (ECM). By feeding small and rotating electrodes aided by ultrasonic rolling, an array of pits can be manufactured, which is called microstructures. However, there still exists the problem...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7696201/ https://www.ncbi.nlm.nih.gov/pubmed/33202701 http://dx.doi.org/10.3390/mi11111002 |
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author | He, Kailei Chen, Xia Wang, Minghuan |
author_facet | He, Kailei Chen, Xia Wang, Minghuan |
author_sort | He, Kailei |
collection | PubMed |
description | Radial ultrasonic rolling electrochemical micromachining (RUR-EMM) is a new method of electrochemical machining (ECM). By feeding small and rotating electrodes aided by ultrasonic rolling, an array of pits can be manufactured, which is called microstructures. However, there still exists the problem of choosing the optimal machining parameters to realize the workpiece machining with high quality and high efficiency. In the present study, response surface methodology (RSM) was proposed to optimize the machining parameters. Firstly, the performance criteria of the RUR-EMM are measured through investigating the effect of working parameters, such as applied voltage, electrode rotation speed, pulse frequency and interelectrode gap (IEG), on material removal amount (MRA) and surface roughness (R(a)). Then, the experimental results are statistically analyzed and modeled through RSM. The regression model adequacies are checked using the analysis of variance. Furthermore, the optimal combination of these parameters has been evaluated and verified by experiment to maximize MRA and minimize R(a). The results show that each parameter has a similar and non-linear influence on the MRA and R(a). Specifically, with the increase of each parameter, MRA increases first and decreases when the parameters reach a certain value. On the contrary, R(a) decreases first and then increases. Under the combined effect of these parameters, the productivity is improved. The experimental value of MRA and R(a) is 0.06006 mm(2) and 51.1 nm, which were 0.8% and 2.4% different from the predicted values. |
format | Online Article Text |
id | pubmed-7696201 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-76962012020-11-29 The Optimal Processing Parameters of Radial Ultrasonic Rolling Electrochemical Micromachining—RSM Approach He, Kailei Chen, Xia Wang, Minghuan Micromachines (Basel) Article Radial ultrasonic rolling electrochemical micromachining (RUR-EMM) is a new method of electrochemical machining (ECM). By feeding small and rotating electrodes aided by ultrasonic rolling, an array of pits can be manufactured, which is called microstructures. However, there still exists the problem of choosing the optimal machining parameters to realize the workpiece machining with high quality and high efficiency. In the present study, response surface methodology (RSM) was proposed to optimize the machining parameters. Firstly, the performance criteria of the RUR-EMM are measured through investigating the effect of working parameters, such as applied voltage, electrode rotation speed, pulse frequency and interelectrode gap (IEG), on material removal amount (MRA) and surface roughness (R(a)). Then, the experimental results are statistically analyzed and modeled through RSM. The regression model adequacies are checked using the analysis of variance. Furthermore, the optimal combination of these parameters has been evaluated and verified by experiment to maximize MRA and minimize R(a). The results show that each parameter has a similar and non-linear influence on the MRA and R(a). Specifically, with the increase of each parameter, MRA increases first and decreases when the parameters reach a certain value. On the contrary, R(a) decreases first and then increases. Under the combined effect of these parameters, the productivity is improved. The experimental value of MRA and R(a) is 0.06006 mm(2) and 51.1 nm, which were 0.8% and 2.4% different from the predicted values. MDPI 2020-11-13 /pmc/articles/PMC7696201/ /pubmed/33202701 http://dx.doi.org/10.3390/mi11111002 Text en © 2020 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 He, Kailei Chen, Xia Wang, Minghuan The Optimal Processing Parameters of Radial Ultrasonic Rolling Electrochemical Micromachining—RSM Approach |
title | The Optimal Processing Parameters of Radial Ultrasonic Rolling Electrochemical Micromachining—RSM Approach |
title_full | The Optimal Processing Parameters of Radial Ultrasonic Rolling Electrochemical Micromachining—RSM Approach |
title_fullStr | The Optimal Processing Parameters of Radial Ultrasonic Rolling Electrochemical Micromachining—RSM Approach |
title_full_unstemmed | The Optimal Processing Parameters of Radial Ultrasonic Rolling Electrochemical Micromachining—RSM Approach |
title_short | The Optimal Processing Parameters of Radial Ultrasonic Rolling Electrochemical Micromachining—RSM Approach |
title_sort | optimal processing parameters of radial ultrasonic rolling electrochemical micromachining—rsm approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7696201/ https://www.ncbi.nlm.nih.gov/pubmed/33202701 http://dx.doi.org/10.3390/mi11111002 |
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