Effectiveness of Minimum Quantity Lubrication in Hard Milling of AISI H13

Effectiveness of Minimum Quantity Lubrication in Hard Milling of AISI H13Effectiveness of Minimum Quantity Lubrication in Hard Milling of AISI H13Effectiveness of Minimum Quantity Lubrication in Hard Milling of AISI H13Effectiveness of Minimum Quantity Lubrication in Hard Milling of AISI H13Effectiveness of Minimum Quantity Lubrication in Hard Milling of AISI H13Effectiveness of Minimum Quantity Lubrication in Hard Milling of AISI H13Effectiveness of Minimum Quantity Lubrication in Hard Milling of AISI H13Effectiveness of Minimum Quantity Lubrication in Hard Milling of AISI H13Effectiveness of Minimum Quantity Lubrication in Hard Milling of AISI H13Effectiveness of Minimum Quantity Lubrication in Hard Milling of AISI H13Effectiveness of Minimum Quantity Lubrication in Hard Milling of AISI H13

國立高雄應用科技大學 機械工程系 博士論文 AISI H13 硬銑削最少量潤滑有效性之研究 Effectiveness of Minimum Quantity Lubrication in Hard Milling of AISI H13 Student: Do The Vinh (杜 勢 榮) Advisor: Dr Quang-Cherng Hsu (許光城 教授) 中華民國 106 年 月 i AISI H13 硬銑削最少量潤滑有效性之研究 Effectiveness of Minimum Quantity Lubrication in Hard Milling of AISI H13 研究生: 杜 勢 榮 指導教授: 許光城 教授 國立高雄應用科技大學 機械工程系 博士論文 A Dissertation Submitted to Institute of Mechanical Engineering National Kaohsiung University of Applied Sciences In Partial Fulfillment of the Requirements For the Degree of Doctor of Philosophy In Mechanical Engineering June 2017 Kaohsiung, Taiwan, Republic of China 中華民國 106 年 月 ii iii 中文摘要 最小量潤滑(MQL)可有效取代濕切及乾切製程，其應用於硬銑削可改善 表面光度、降低刀具磨耗、增加刀具壽命及降低切削溫度等優點。 本研究分為兩部分：第一部分以降低表面粗度值為品質目標利用田口 方法找出 AISI H13 於硬銑削下之最佳切削參數。本研究以槽銑加工進行 研究，採用 L9 直交表進行實驗配置並以訊噪比(S/N)及變異數分析(ANOVA) 分析最小量潤滑參數(切消液種類、壓力及流量)對表面光度的影響。結果 顯示其最佳參數為流量 50 ml/h 且壓力 kg/cm2 之水溶性切削液，其流量 與壓力貢獻度經變異數分析後依序為 68.13%及 30.19%。 在第二部分之研究主要基於表面粗糙度及切削力來驗證最小量潤滑之 效率，以乾切與最小量潤滑之切削力及表面粗糙度做比較，選用 L27 直交表 進行實驗規劃，運用反應曲面法及變異數分析來分析切削參數對切削力及 表面粗糙度的影響。結果顯示在乾切與最小潤滑的條件下進給率及切深皆 對表面粗糙度影響最大。切削力分量主要受切削深度影響其次為進給速率。 當切削條件為高切速、低進給與低切深且低硬度之材料即可獲得較良好的 表面粗糙度和最小的切削力。而最小量潤滑切削可提供較好的表面粗糙度 及降低刀具磨耗。以統計模型建立出預測模型用以預測乾切與最小量潤滑 條件下之切削力和表面粗糙度，其結果顯示最小量潤滑相較於乾切條件下 更具有顯著的效果。 關鍵字：最小量潤滑、優化、切削力、表面粗糙度、刀具磨耗、硬銑削、 田口方法、反應曲面法 iv Effectiveness of Minimum Quantity Lubrication in Hard Milling of AISI H13 Advisors: Prof Quang-Cherng Hsu Student：Do The Vinh Institute of Mechanical Engineering National Kaohsiung University of Applied Sciences ABSTRACT As a successful alternative to flood coolant processing and dry cutting, the minimum quantity lubricant (MQL) has already been applied to hard milling for improvement of surface finish, reduction of tool wear, an increase of tool life, reduction of cutting temperature, etc This research was divided into two parts In the first part, Taguchi method was used to find the optimal values of MQL condition in the hard milling of AISI H13 with consideration of improved surface roughness Slot milling was selected for the investigation as an operation that is commonly applied for machining of the closed slots or pockets and grooves, etc Taguchi’s L9 array was used to design the experiments The signal-to-noise (S/N) ratio and analysis of variance (ANOVA) were utilized to analyze the influence of the performance characteristics of MQL parameters (i.e., cutting fluid type, pressure, and fluid flow) on surface finish In the results section, the water-soluble oil lubricant, the 50 ml/h fluid flow and the kg/cm2 pressures provided the best results for surface roughness in hard-milling of AISI H13 Lubricant and pressure of MQL condition are determined to be the most influential factors giving a statistically significant effect on machined surfaces The pressure factor contributed 68.13 % and the lubricant factor contributed 30.19 % of the total effect The effect of them v carried statistical significance The three parameters of MQL conditions explained 99.76 % of the variability in surface roughness In the second part, the research objective is to demonstrate the efficiency of MQL based on certain process parameters such as surface roughness and cutting force A comparative analysis was done to prove the effectiveness of MQL versus dry cutting The characteristics of the cutting force and the surface roughness obtained under dry cutting and MQL condition were experimentally investigated The experiments were conducted using the L27 orthogonal array of Taguchi’s experimental design technique The response surface methodology (RSM) and analysis of variance (ANOVA) were employed for analysis the influence of cutting parameters (i.e., cutting speed, feed rate, depth-of-cut and hardness of work-piece) on the cutting force and the surface roughness As the result, under both cutting conditions (MQL and dry), feed rate and depth of cut are the most influential variables regarding surface roughness The cutting force components get affected mostly by depth of cut followed by feed rate Higher cutting speed, lower feed rate, lower depth of cut and lower work-piece hardness applied lead to good surface roughness and minimum cutting force MQL cutting provided better surface roughness and reduced tool wear The difference of values of cutting force components under two cutting conditions (MQL and dry) is negligible in short machining time The statistical models to predict cutting force and surface roughness under dry cutting and MQL condition were established The results of the research showed the outstanding effectiveness of MQL compared to dry cutting Keywords: Minimum quantity lubricant, optimization, cutting force, surface roughness, tool wear, hard milling, Taguchi method, response surface methodology vi ACKNOWLEDGMENTS The fulfillment of over four years of study at National Kaohsiung University of Applied Sciences (KUAS) has brought me into closer relations with many enthusiastic people who wholeheartedly devoted their time, energy, and support to help me during my studies Therefore, this is my opportunity to acknowledge my great debt of thanks to them I wish to express my thanks and gratitude to my academic supervisor, Prof Dr Quang-Cherng Hsu, for his continuous guidance, valuable advice, and helpful supports during my studies He has always been supportive of my research work and gave me the freedom to fully explore the different research areas related with MQL hard milling I would also like to thank Prof Yung-Chou Kao, my first supervisor, for his help and advice during my first study time at KUAS I wish to acknowledge my deepest thanks to President of KUAS and Office of International Affairs for giving me a great opportunity, necessary scholarships to study at KUAS and many enthusiastic helps during my time in KUAS I am also particularly grateful to Thai Nguyen University provided me unflagging encouragement, continuous helps and support to complete this course My gratitude also goes to all of the teachers, Dean and staffs of Department of Mechanical Engineering for their devoted teaching, great helping and thoughtful serving during my study in ME I would also like to express my sincere gratitude to all of my colleagues at the Precision and Nano Engineering Laboratory, Department of Mechanical Engineering, KUAS I would specially like to thank Mr Ye Jhan Hong, Mr Li Wen Hsiung and Mr Wei Lin for their great helps in my experimental process vii I want to express my sincere thanks to all my Vietnamese friends in KUAS for their helpful sharing and precious helping me over the past time I also wish to express my gratitude to all those who directly or indirectly helped me during my study in KUAS Finally, my special thanks to my dad Đỗ Văn Kiểu and my mom Nguyễn Thị Hà, to my brother Đỗ Minh Khoa, to my adorable wife Nguyễn Thị Nguyên, to lovely little daughter Đỗ Khánh Linh, who is the most motivation for me over years in Taiwan viii CONTENTS 中文摘要 iv ABSTRACT v ACKNOWLEDGMENTS vii CONTENTS ix LIST OF FIGURES xiii LIST OF TABLES xvi NOMENCLATURE xvii Chapter INTRODUCTION 1.1 Motivation of the research 1.2 Objective of the research 1.3 Scopes of the research 1.4 Organization of the Dissertation Chapter BACKGROUND 2.1 Hard machining 2.1.1 Overview 2.1.1.1 Concepts of hard machining 2.1.1.2 Advantages and disadvantages 2.1.2 Basic operations in hard machining 2.1.2.1 Hard turning 2.1.2.2 Hard milling 10 2.1.2.3 Other operations 11 2.1.3 The characterization of hard machining 13 ix 2.1.3.1 Cutting temperature 13 2.1.3.2 Surface roughness 14 2.1.3.3 Cutting force 15 2.1.3.4 Tool wear 17 2.2 Cooling and lubrication in metal cutting 19 2.2.1 Functions of cutting fluid 19 2.2.1.1 Cooling 20 2.2.1.2 Lubrication 22 2.2.2 Types of cutting fluid 22 2.2.2.1 Neat cutting oil 23 2.2.2.2 Soluble oil 24 2.2.2.3 Semisynthetic 25 2.2.2.4 Synthetic 26 2.2.3 Cooling/lubrication methods 26 2.2.3.1 Wet machining method 26 2.2.3.2 Dry machining method 28 2.2.3.3 Minimum quantity lubrication method 28 2.3 Minimum quantity lubrication 29 2.3.1 Introduction 29 2.3.2 Principles of MQL system 30 2.3.3 The MQL systems 32 2.3.4 The lubricant feeding forms in MQL 33 2.3.4.1 Internal feeding form 33 2.3.4.2 External feeding form 34 x bien_Ra= 1.58318-(0.00561086*bien_v)-(20.44*bien_f)- (0.102333*bien_d)-(0.0538385*bien_H)-(4.93827*Math.pow(10,5)*bien_v*bien_v)+ (85.5556*bien_f*bien_f)- (0.0444444*bien_d*bien_d)+(0.000422222*bien_H*bien_H)+(0.172889*bien_v *bien_f)(0.0072*bien_v*bien_d)+(0.000204741*bien_v*bien_H)+(9.78889*bien_f* bien_d)+(0.301333*bien_f*bien_H)+(0.0142667*bien_d*bien_H); bien_Fx= 1209.97-(3.20958*bien_v)-(6108.19*bien_f)- (43.7167*bien_d)-(47.354*bien_H)-(0.00602469*bien_v*bien_v)(6055.56*bien_f*bien_f) - (243.472*bien_d*bien_d)+(0.427778*bien_H*bien_H)(39.5704*bien_v*bien_f)-(1.54*bien_v*bien_d)+(0.0865778*bien_v*bien_H)+ (5113.33*bien_f*bien_d)+(206.933*bien_f*bien_H)+(10.7422*bien_d*bien _H); bien_Fy= 539.515- (6.97595*bien_v)+(3907.41*bien_f)+(137.439*bien_d)(18.9634*bien_H)+(0.0196049*bien_v*bien_v)-(148889*bien_f*bien_f)(55.9722*bien_d*bien_d)+(0.0964444*bien_H*bien_H)(46.8741*bien_v*bien_f)-(3.88*bien_v*bien_d)+(0.138963*bien_v*bien_H)+ (272.222*bien_f*bien_d)+(154.533*bien_f*bien_H)+(8.82444*bien_d*bien _H); bien_Fz= 131.319-(0.800642*bien_v)- (43.3704*bien_f)+(13.3907*bien_d)(5.04696*bien_H)+(0.0014321*bien_v*bien_v)-(13277.8*bien_f*bien_f)(22.3611*bien_d*bien_d)+(0.0408889*bien_H*bien_H)(6.07407*bien_v*bien_f)(0.436296*bien_v*bien_d)+(0.0169185*bien_v*bien_H)+ 116 (345.556*bien_f*bien_d)+(25.3778*bien_f*bien_H)+(1.34444*bien_d*bien _H); } /////////////////////////////////////////////////////////////////////////////////////////////////////////////// private void ptTinhTheoMQL(){ bien_Ra= 1.28831-(0.00744864*bien_v)-(15.8793*bien_f)- (0.0482593*bien_d)-(0.0404059*bien_H)(2.93827*Math.pow(10,-5)*bien_v*bien_v)+(65.5556*bien_f*bien_f)(0.0194444*bien_d*bien_d)+ (0.000302222*bien_H*bien_H)+(0.156148*bien_v*bien_f)(0.00582963*bien_v*bien_d)+ (0.000196148*bien_v*bien_H)+(7.41111*bien_f*bien_d)+(0.205778*bien_f *bien_H)+(0.0106444*bien_d*bien_H); bien_Fx= 1141.03-(3.08148*bien_v)- (5162.44*bien_f)+(54.413*bien_d)-(45.7427*bien_H)(0.00474074*bien_v*bien_v)-(32333.3*bien_f*bien_f)(263.75*bien_d*bien_d)+(0.415333*bien_H*bien_H)-(30.2222*bien_v*bien_f)(2.3763*bien_v*bien_d)+(0.084563*bien_v*bien_H)+(4465.56*bien_f*bien_d) +(201.644*bien_f*bien_H)+(10.2*bien_d*bien_H); bien_Fy= 527.606- (7.87711*bien_v)+(6821.74*bien_f)+(157.309*bien_d)(18.8253*bien_H)+(0.0276296*bien_v*bien_v)- (160833*bien_f*bien_f)- (39.5833*bien_d*bien_d)+(0.102*bien_H*bien_H)-(45.3185*bien_v*bien_f)(4.3437*bien_v*bien_d)+(0.142104*bien_v*bien_H)(832.222*bien_f*bien_d)+(107.156*bien_f*bien_H)+(9.15778*bien_d*bien_H); bien_Fz= 116.209- (0.733062*bien_v)+(147.333*bien_f)+(12.3204*bien_d)- 117 (4.52904*bien_H)+(0.00145679*bien_v*bien_v)-(13888.9*bien_f*bien_f)(20.9722*bien_d*bien_d)+(0.0364444*bien_H*bien_H)(5.55556*bien_v*bien_f)(0.459259*bien_v*bien_d)+(0.015437*bien_v*bien_H)+(251.111*bien_f*bi en_d)+(21.5556*bien_f*bien_H)+(1.4*bien_d*bien_H); } /////////////////////////////////////////////////////////////////////////////////////////////////////////////// private void ptHienThiKetQua(){ jTFRa.setText(String.valueOf(dtDF.format(bien_Ra))); jTFFx.setText(String.valueOf(dtDF.format(bien_Fx))); jTFFy.setText(String.valueOf(dtDF.format(bien_Fy))); jTFFz.setText(String.valueOf(dtDF.format(bien_Fz))); } } 118 REFERENCE [1] S Afazov, S Ratchev, and J Segal, "Prediction and experimental validation of micro-milling cutting forces of AISI H13 steel at hardness between 35 and 60 HRC," The International Journal of Advanced Manufacturing Technology, vol 62, pp 887-899, 2012 [2] T Ding, S Zhang, Y Wang, and X Zhu, "Empirical models and optimal cutting parameters for cutting forces and 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chapter, an overview of hard machining, cooling and lubrication in metal cutting, and overview of minimum quantity lubrication were described 2.1 Hard machining 2.1.1