Optimization of Minimum Quantity Lubricant Conditions and Cutting Parameters in Hard Milling of AISI H13 Steel

As a successful solution applied to hard machining, the minimum quantity lubricant (MQL) has already been established as an alternative to flood coolant processing. The optimization of MQL parameters and cutting parameters under MQL condition are essential and pressing. The study was divided into tw...

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Main Authors: The-Vinh Do, Quang-Cherng Hsu
Format: Article
Language:English
Published: MDPI AG 2016-03-01
Series:Applied Sciences
Subjects:
MQL
Online Access:http://www.mdpi.com/2076-3417/6/3/83
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spelling doaj-62a2f0b7b3c749bba39efda16185a73d2020-11-24T23:06:36ZengMDPI AGApplied Sciences2076-34172016-03-01638310.3390/app6030083app6030083Optimization of Minimum Quantity Lubricant Conditions and Cutting Parameters in Hard Milling of AISI H13 SteelThe-Vinh Do0Quang-Cherng Hsu1Department of Mechanical Engineering, National Kaohsiung University of Applied Sciences, 415 Chien Kung Road, Sanmin District, Kaohsiung 80778, TaiwanDepartment of Mechanical Engineering, National Kaohsiung University of Applied Sciences, 415 Chien Kung Road, Sanmin District, Kaohsiung 80778, TaiwanAs a successful solution applied to hard machining, the minimum quantity lubricant (MQL) has already been established as an alternative to flood coolant processing. The optimization of MQL parameters and cutting parameters under MQL condition are essential and pressing. The study was divided into two parts. In the first part of this study, the Taguchi method was applied to find the optimal values of MQL condition in the hard milling of AISI H13 with consideration of reduced surface roughness. The L9 orthogonal array, the signal-to-noise (S/N) ratio and analysis of variance (ANOVA) were employed to analyze the effect of the performance characteristics of MQL parameters (i.e., cutting fluid type, pressure, and fluid flow) on good surface finish. In the results section, lubricant and pressure of MQL condition are determined to be the most influential factors which give a statistically significant effect on machined surfaces. A verifiable experiment was conducted to demonstrate the reliability of the results. In the second section, the optimized MQL parameters were applied in a series of experiments to find out cutting parameters of hard milling. The Taguchi method was also used to optimize the cutting parameters in order to obtain the best surface roughness. The design of the experiment (DOE) was implemented by using the L27 orthogonal array. Based on an analysis of the signal-to-noise response and ANOVA, the optimal values of cutting parameters (i.e., cutting speed, feed rate, depth-of-cut and hardness of workpiece) were introduced. The results of the present work indicate feed rate is the factor having the most effect on surface roughness.http://www.mdpi.com/2076-3417/6/3/83optimizationMQLhard millingTaguchi methodANOVA
collection DOAJ
language English
format Article
sources DOAJ
author The-Vinh Do
Quang-Cherng Hsu
spellingShingle The-Vinh Do
Quang-Cherng Hsu
Optimization of Minimum Quantity Lubricant Conditions and Cutting Parameters in Hard Milling of AISI H13 Steel
Applied Sciences
optimization
MQL
hard milling
Taguchi method
ANOVA
author_facet The-Vinh Do
Quang-Cherng Hsu
author_sort The-Vinh Do
title Optimization of Minimum Quantity Lubricant Conditions and Cutting Parameters in Hard Milling of AISI H13 Steel
title_short Optimization of Minimum Quantity Lubricant Conditions and Cutting Parameters in Hard Milling of AISI H13 Steel
title_full Optimization of Minimum Quantity Lubricant Conditions and Cutting Parameters in Hard Milling of AISI H13 Steel
title_fullStr Optimization of Minimum Quantity Lubricant Conditions and Cutting Parameters in Hard Milling of AISI H13 Steel
title_full_unstemmed Optimization of Minimum Quantity Lubricant Conditions and Cutting Parameters in Hard Milling of AISI H13 Steel
title_sort optimization of minimum quantity lubricant conditions and cutting parameters in hard milling of aisi h13 steel
publisher MDPI AG
series Applied Sciences
issn 2076-3417
publishDate 2016-03-01
description As a successful solution applied to hard machining, the minimum quantity lubricant (MQL) has already been established as an alternative to flood coolant processing. The optimization of MQL parameters and cutting parameters under MQL condition are essential and pressing. The study was divided into two parts. In the first part of this study, the Taguchi method was applied to find the optimal values of MQL condition in the hard milling of AISI H13 with consideration of reduced surface roughness. The L9 orthogonal array, the signal-to-noise (S/N) ratio and analysis of variance (ANOVA) were employed to analyze the effect of the performance characteristics of MQL parameters (i.e., cutting fluid type, pressure, and fluid flow) on good surface finish. In the results section, lubricant and pressure of MQL condition are determined to be the most influential factors which give a statistically significant effect on machined surfaces. A verifiable experiment was conducted to demonstrate the reliability of the results. In the second section, the optimized MQL parameters were applied in a series of experiments to find out cutting parameters of hard milling. The Taguchi method was also used to optimize the cutting parameters in order to obtain the best surface roughness. The design of the experiment (DOE) was implemented by using the L27 orthogonal array. Based on an analysis of the signal-to-noise response and ANOVA, the optimal values of cutting parameters (i.e., cutting speed, feed rate, depth-of-cut and hardness of workpiece) were introduced. The results of the present work indicate feed rate is the factor having the most effect on surface roughness.
topic optimization
MQL
hard milling
Taguchi method
ANOVA
url http://www.mdpi.com/2076-3417/6/3/83
work_keys_str_mv AT thevinhdo optimizationofminimumquantitylubricantconditionsandcuttingparametersinhardmillingofaisih13steel
AT quangchernghsu optimizationofminimumquantitylubricantconditionsandcuttingparametersinhardmillingofaisih13steel
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