Prediction and optimization of surface roughness in grinding of S50C carbon steel using minimum quantity lubrication of Vietnamese peanut oil

This experimental research aimed to build the regression model of grinding S50C carbon steel based on a Regression Optimizer. The workpiece specimens were JIS S50C carbon steel that was hardened at 52HRC. Taguchi L27 orthogonal array was performed with 5 3-levels-factors. The studied factors were co...

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Autores principales:	Duong Nguyen Thuy, Dung Hoang Tien, Canh Nguyen Van, Hoanh Dao Ngoc, Hien Do Minh, Nguyen Van Thien
Formato:	article
Lenguaje:	EN
Publicado:	Institut za istrazivanja i projektovanja u privredi 2021
Materias:	grinding minimum quantity lubricant optimization regression optimizer multi-response optimization Technology T Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/c26738e7bf7f46d585e354446a558116
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spelling	oai:doaj.org-article:c26738e7bf7f46d585e354446a5581162021-12-05T21:23:13ZPrediction and optimization of surface roughness in grinding of S50C carbon steel using minimum quantity lubrication of Vietnamese peanut oil1451-41171821-319710.5937/jaes0-30580https://doaj.org/article/c26738e7bf7f46d585e354446a5581162021-01-01T00:00:00Zhttps://scindeks-clanci.ceon.rs/data/pdf/1451-4117/2021/1451-41172103814D.pdfhttps://doaj.org/toc/1451-4117https://doaj.org/toc/1821-3197This experimental research aimed to build the regression model of grinding S50C carbon steel based on a Regression Optimizer. The workpiece specimens were JIS S50C carbon steel that was hardened at 52HRC. Taguchi L27 orthogonal array was performed with 5 3-levels-factors. The studied factors were combining cutting parameters, such as cutting speed, feed rate, depth of cut, and lubricant parameters, including air coolant flow rate Q and air pressure P. The results show that cutting parameters includes workpiece velocity Vw, feed rate f, and depth of cut ap, influence the most on surface roughness Ra , Root Mean Square Roughness Rq, and Mean Roughness Depth Rz. By contrast, the influence of lubrication parameters is fuzzy. Therefore, this present work focused on predicting and optimizing Ra, Rz, Rq in surface grinding of JSI S50C carbon steel using MQL of peanut oil. In this work, combining of grinding parameters and lubrication parameters were considered as input factors. The regression models of Ra , Rz, and Rq were obtained using Minitab 19 by Regression Optimizer tool, and then the multi-objective optimization problem was solved. The present findings have shown that Vietnamese vegetable peanut oil could be considered as the lubricant in the grinding process. The optimum grinding and lubricant parameters as following: the workpiece velocity Vw of 5 m/min, feed rate f of 3mm/stroke, depth of cut of 0.005mm and oil flow rate, air pressure of 91.94 ml/h, 1 MPa, respectively. Corresponding to the surface roughness Ra , Root Mean Square Roughness Rq , and Mean Roughness Depth Rz of 0.6512mm, 4.592mm, 0.8570mm, respectively.Duong Nguyen ThuyDung Hoang TienCanh Nguyen VanHoanh Dao NgocHien Do MinhNguyen Van ThienInstitut za istrazivanja i projektovanja u privrediarticlegrindingminimum quantity lubricantoptimizationregression optimizermulti-response optimizationTechnologyTEngineering (General). Civil engineering (General)TA1-2040ENIstrazivanja i projektovanja za privredu, Vol 19, Iss 3, Pp 814-821 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	grinding minimum quantity lubricant optimization regression optimizer multi-response optimization Technology T Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	grinding minimum quantity lubricant optimization regression optimizer multi-response optimization Technology T Engineering (General). Civil engineering (General) TA1-2040 Duong Nguyen Thuy Dung Hoang Tien Canh Nguyen Van Hoanh Dao Ngoc Hien Do Minh Nguyen Van Thien Prediction and optimization of surface roughness in grinding of S50C carbon steel using minimum quantity lubrication of Vietnamese peanut oil
description	This experimental research aimed to build the regression model of grinding S50C carbon steel based on a Regression Optimizer. The workpiece specimens were JIS S50C carbon steel that was hardened at 52HRC. Taguchi L27 orthogonal array was performed with 5 3-levels-factors. The studied factors were combining cutting parameters, such as cutting speed, feed rate, depth of cut, and lubricant parameters, including air coolant flow rate Q and air pressure P. The results show that cutting parameters includes workpiece velocity Vw, feed rate f, and depth of cut ap, influence the most on surface roughness Ra , Root Mean Square Roughness Rq, and Mean Roughness Depth Rz. By contrast, the influence of lubrication parameters is fuzzy. Therefore, this present work focused on predicting and optimizing Ra, Rz, Rq in surface grinding of JSI S50C carbon steel using MQL of peanut oil. In this work, combining of grinding parameters and lubrication parameters were considered as input factors. The regression models of Ra , Rz, and Rq were obtained using Minitab 19 by Regression Optimizer tool, and then the multi-objective optimization problem was solved. The present findings have shown that Vietnamese vegetable peanut oil could be considered as the lubricant in the grinding process. The optimum grinding and lubricant parameters as following: the workpiece velocity Vw of 5 m/min, feed rate f of 3mm/stroke, depth of cut of 0.005mm and oil flow rate, air pressure of 91.94 ml/h, 1 MPa, respectively. Corresponding to the surface roughness Ra , Root Mean Square Roughness Rq , and Mean Roughness Depth Rz of 0.6512mm, 4.592mm, 0.8570mm, respectively.
format	article
author	Duong Nguyen Thuy Dung Hoang Tien Canh Nguyen Van Hoanh Dao Ngoc Hien Do Minh Nguyen Van Thien
author_facet	Duong Nguyen Thuy Dung Hoang Tien Canh Nguyen Van Hoanh Dao Ngoc Hien Do Minh Nguyen Van Thien
author_sort	Duong Nguyen Thuy
title	Prediction and optimization of surface roughness in grinding of S50C carbon steel using minimum quantity lubrication of Vietnamese peanut oil
title_short	Prediction and optimization of surface roughness in grinding of S50C carbon steel using minimum quantity lubrication of Vietnamese peanut oil
title_full	Prediction and optimization of surface roughness in grinding of S50C carbon steel using minimum quantity lubrication of Vietnamese peanut oil
title_fullStr	Prediction and optimization of surface roughness in grinding of S50C carbon steel using minimum quantity lubrication of Vietnamese peanut oil
title_full_unstemmed	Prediction and optimization of surface roughness in grinding of S50C carbon steel using minimum quantity lubrication of Vietnamese peanut oil
title_sort	prediction and optimization of surface roughness in grinding of s50c carbon steel using minimum quantity lubrication of vietnamese peanut oil
publisher	Institut za istrazivanja i projektovanja u privredi
publishDate	2021
url	https://doaj.org/article/c26738e7bf7f46d585e354446a558116
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Prediction and optimization of surface roughness in grinding of S50C carbon steel using minimum quantity lubrication of Vietnamese peanut oil

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