scholarly journals ASSESSMENT OF SURFACE ROUGHNESS IN MQL ASSISTED TURNING PROCESS OF TITANIUM ALLOY WITH APPLICATION OF TOPSIS-AHP METHOD

2018 ◽  
Vol 18 (2) ◽  
pp. 98-106
Author(s):  
Marian BARTOSZUK ◽  
Munish Kumar GUPTA
Keyword(s):  
Surface Roughness ◽  
Titanium Alloys ◽  
Feed Rate ◽  
Cutting Speed ◽  
Minimum Quantity Lubrication ◽  
Cutting Parameters ◽  
Machining Parameters ◽  
Turning Process ◽  
Ahp Method ◽  
Approach Angle

The optimization of surface roughness values considered as one of the most significant issues regarding turning process of titanium alloys with the use of minimum quantity lubrication (MQL) method. With such an aim in mind, the application of TOPSIS-AHP method is implemented in order to establish the most favourable cutting parameters for the following values of surface roughness: Ra, Rq and Rz in machining of titanium alloys regarding MQL conditions. The proposed methodology consists of the two stages. At the beginning, tests on turning process were performed on CNC lathe, taking feed rate, approach angle, and cutting speed as input parameters. Then, the TOPSIS-AHP method was applied on the given experimental data and the optimum machining parameters were determined. The findings from current investigations showed that, lower values of cutting speed, feed rate and middle value of approach angle shows the optimal results.

scholarly journals Investigations on Surface Roughness and Tool Wear Characteristics in Micro-Turning of Ti-6Al-4V Alloy

Materials ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 2998 ◽  
Author(s):  
Kubilay Aslantas ◽  
Mohd Danish ◽  
Ahmet Hasçelik ◽  
Mozammel Mia ◽  
Munish Gupta ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Removal Rate ◽  
Cutting Speed ◽  
Small Diameter ◽  
Cutting Parameters ◽  
Ti6al4v Alloy ◽  
Depth Of Cut ◽  
Turning Process ◽  
Micro Turning

Micro-turning is a micro-mechanical cutting method used to produce small diameter cylindrical parts. Since the diameter of the part is usually small, it may be a little difficult to improve the surface quality by a second operation, such as grinding. Therefore, it is important to obtain the good surface finish in micro turning process using the ideal cutting parameters. Here, the multi-objective optimization of micro-turning process parameters such as cutting speed, feed rate and depth of cut were performed by response surface method (RSM). Two important machining indices, such as surface roughness and material removal rate, were simultaneously optimized in the micro-turning of a Ti6Al4V alloy. Further, the scanning electron microscope (SEM) analysis was done on the cutting tools. The overall results depict that the feed rate is the prominent factor that significantly affects the responses in micro-turning operation. Moreover, the SEM results confirmed that abrasion and crater wear mechanism were observed during the micro-turning of a Ti6Al4V alloy.

Effects of Machining Parameters on Surface Roughness when Ultra-High Precision Diamond Turning RSA443 Optical Aluminum

2019 ◽  
Vol 287 ◽  
pp. 30-34
Author(s):  
Zwelinzima Mkoko ◽  
Khaled Abou-El-Hossein
Keyword(s):  
Surface Roughness ◽  
Silicon Content ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Diamond Turning ◽  
Machining Parameters ◽  
Turning Process ◽  
Optical Components ◽  
Box Behnken Design ◽  
Factors Influencing

In the globally competitive environment, surface roughness and finer tolerances are becoming stringent and certainly most critical for optical components. The aim of this study is to determine the effects of diamond turning process parameters on surface finish when diamond turning RSA 443 alloy having high silicon content. This alloy is a new grade of aluminum that has a potential to be used for production of various optical components. The experiments were conducted based on the Box-Behnken design with three diamond-turning parameters varied at three levels. A mathematical regression model was developed for predicting surface roughness. Further, the analysis of variance was used to analyze the influence of cutting parameters and their interaction in machining. The developed prediction model reveals that cutting speed and feed rate are the most dominant diamond turning factors influencing surface roughness.

Investigations on Surface Roughness Measurement in Minimum Quantity Lubrication Turning of Titanium Alloys Using Response Surface Methodology and Box–Cox Transformation

2016 ◽  
Vol 16 (2) ◽  
pp. 75-88 ◽  
Author(s):  
Munish Kumar Gupta ◽  
P. K. Sood ◽  
Vishal S. Sharma
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Flow Rate ◽  
Feed Rate ◽  
Cutting Speed ◽  
Minimum Quantity Lubrication ◽  
Machining Parameters ◽  
Minimum Quantity ◽  
Box Cox Transformation

AbstractIn the present work, an attempt has been made to establish the accurate surface roughness (Ra, Rq and Rz) prediction model using response surface methodology with Box–Cox transformation in turning of Titanium (Grade-II) under minimum quantity lubrication (MQL) conditions. This surface roughness model has been developed in terms of machining parameters such as cutting speed, feed rate and approach angle. Firstly, some experiments are designed and conducted to determine the optimal MQL parameters of lubricant flow rate, input pressure and compressed air flow rate. After analyzing the MQL parameter, the final experiments are performed with cubic boron nitride (CBN) tool to optimize the machining parameters for surface roughness values i. e., Ra, Rq and Rz using desirability analysis. The outcomes demonstrate that the feed rate is the most influencing factor in the surface roughness values as compared to cutting speed and approach angle. The predicted results are fairly close to experimental values and hence, the developed models using Box-Cox transformation can be used for prediction satisfactorily.

Researches Regarding the Influence of Cutting Regime on Processed Surface in Aluminum Alloys Turning Process

2015 ◽  
Vol 808 ◽  
pp. 15-20
Author(s):  
Adrian Trif ◽  
Marian Borzan ◽  
Alexandru Popan ◽  
Domniţa Fraţilă ◽  
Adriana Rus ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Surface Roughness ◽  
Aluminum Alloy ◽  
Aluminum Alloys ◽  
Statistical Method ◽  
Surface Quality ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Turning Process

The main purpose of this paper is to analyze the influence of cutting regime parameters in case of dry turning of an aluminum alloy. For turning process of the aluminum alloy was used Sandvik insert DCGX 11 T3 08 Al H10. The influence of the main cutting parameters on the surface quality was analyzed using a statistical method (ANOVA) used to test differences between two or more means. Based on a mathematical model can be calculated the surface roughness taking into account the cutting speed, the feed rate and the depth of cutting.

scholarly journals Effects of Parameters of Machining on Cutting Force and Roughness when Machining AZ31 Magnesium Alloy

2019 ◽  
Vol 9 (2) ◽  
pp. 4756-4758
Keyword(s):  
Cutting Force ◽  
Feed Rate ◽  
High Speed ◽  
Cutting Speed ◽  
Minimum Quantity Lubrication ◽  
Cutting Parameters ◽  
Machining Process ◽  
Mg Alloy ◽  
Machining Parameters ◽  
Machining Processes

This project was done to learn the effects of cutting parameters on cutting force and roughness (surface roughnes) of AZ31 magnesium (Mg) alloy. Machining parameters involved in this project are cutting speed, feed rate, and lubrication methods. Deckel Maho DMU 50 eVolution high speed milling machine was using and uncoated carbide button insert was used as the cutting tool. Cutting force was measured during the milling process and roughness was measured after that and cleaning process to ensure no interference that would conflicted the results. The best machining parameters identified when feed rate at 0.05 mm per tooth, cutting speed are at 600 m per min, and minimum quantity lubrication was applied during the machining process. From analysis of variance (ANOVA) table generated by Minitab software, this project can conclude that feed rate, cutting speed, and lubrication methods are significant to cutting force and roughness when machining AZ31 Mg Alloy Therefore, the relationship of surface roughness and cutting force should be taken as a major key point in machining processes. In the automotive field, magnesium was used to fabricate an engine that place at front body due to reduce the weight of vehicle. This design can increase performance and balancing of weight [1].

scholarly journals PENENTUAN KECEPATAN PEMOTONGAN EFEKTIF BERDASARKAN NILAI KEKASARAN PERMUKAAN MATERIAL AA-7075 PADA PROSES FACE MILLING

POROS ◽  
2021 ◽  
Vol 17 (1) ◽  
pp. 51
Author(s):  
Sobron Y. Lubis ◽  
Rosehan Rosehan ◽  
Musa Law
Keyword(s):  
Surface Roughness ◽  
Surface Quality ◽  
Feed Rate ◽  
Tooth Development ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Face Milling ◽  
Machining Parameters ◽  
Aa 7075 ◽  
Aluminum Alloy 7075

During face milling machining, several machining parameters such as feed rate and cuttingspeed determine the surface quality of the workpiece produced by the process. The selection of the rightparameters will lead to the surface quality as planned. Therefore, to improve machining effectiveness, amethod is needed to determine the appropriate machining parameters to produce the desired surfacequality. This research was conducted using a milling machine, five variations of cutting speed and fivevariations of feed rate were used to cut the workpiece aluminum alloy 7075. After machining, the surfaceroughness was measured using a surface test. The surface roughness value is then substituted into thefeed rate equation and effective cutting speed. By finding effective cutting parameters, the machiningprocess will be more efficient and effective without using unnecessary resources. From the results of thestudy note that the development equation to determine the feed rate based on the value of surfaceroughness is ???? = 0,6????√???? ????????0.443mm/tooth. Development equation to determine the effective cutting speedbased on Surface roughness value is ???????? = 3.0686????????0.124 mm/min

Optimization of Cutting Parameters for Turning Operation of Titanium Alloy Ti-6Al-4V Material Workpiece Using the Taguchi Method

2013 ◽  
Vol 685 ◽  
pp. 57-62
Author(s):  
Seyyed Pedram Shahebrahimi ◽  
Abdolrahman Dadvand
Keyword(s):  
Surface Roughness ◽  
Titanium Alloy ◽  
Taguchi Method ◽  
Surface Finish ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Material Tool

One of the most important issues in turning operations is to choose suitable parameters in order to achieve a desired surface finish. The surface finish in machining operation depends on many parameters such as workpiece material, tool material, tool coating, machining parameters, etc. The purpose of this research is to focus on the analysis of optimum cutting parameters to get the lowest surface roughness in turning Titanium alloy Ti-6Al-4V with the insert with the standard code DNMG 110404 under dry cutting condition, by the Taguchi method. The turning parameters are evaluated as cutting speed of 14, 20 and 28 m/min, feed rate of 0.12, 0.14 and 0.16 mm/rev, depth of cut of 0.3, 0.6 and 1 mm, each at three levels. The Experiment was designed using the Taguchi method and 9 experiments were conducted by this process. The results are analyzed using analysis of variance method (ANOVA). The results of analysis show that the depth of cut has a significant role to play in producing lower surface roughness that is about 63.33% followed by feed rate about 30.25%, and cutting speed has less contribution on the surface roughness. Also it was realized that with the use of the confirmation test, the surface roughness improved by 227% from its initial state.

Optimization of Surface Roughness in Turning Operation Using Firefly Algorithm

2015 ◽  
Vol 815 ◽  
pp. 268-272 ◽  
Author(s):  
Nur Farahlina Johari ◽  
Azlan Mohd Zain ◽  
Noorfa Haszlinna Mustaffa ◽  
Amirmudin Udin
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Firefly Algorithm ◽  
Volume Fraction ◽  
Optimization Problems ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Machining Time

Recently, Firefly Algorithm (FA) has become an important technique to solve optimization problems. Various FA variants have been developed to suit various applications. In this paper, FA is used to optimize machining parameters such as % Volume fraction of SiC (V), cutting speed (S), feed rate (F), depth of cut (D) and machining time (T). The optimal machining cutting parameters estimated by FA that lead to a minimum surface roughness are validated using ANOVA test.

Investigating and Modeling the Machinability of Al 6061 Using Response Surface Methodology

2015 ◽  
Vol 761 ◽  
pp. 267-272
Author(s):  
Basim A. Khidhir ◽  
Ayad F. Shahab ◽  
Sadiq E. Abdullah ◽  
Barzan A. Saeed
Keyword(s):  
Mathematical Model ◽  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Feed Rate ◽  
Cutting Speed ◽  
Effect Of Temperature ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Turning Process

Decreasing the effect of temperature, surface roughness and vibration amplitude during turning process will improve machinability. Mathematical model has been developed to predict responses of the surface roughness, temperature and vibration in relation to machining parameters such as the cutting speed, feed rate, and depth of cut. The Box-Behnken First order and second-order response surface methodology was employed to create a mathematical model, and the adequacy of the model was verified using analysis of variance. The experiments were conducted on aluminium 6061 by cemented carbide. The direct and interaction effect of the machining parameters with responses were analyzed. It was found that the feed rate, cutting speed, and depth of cut played a major role on the responses, such as the surface roughness and temperature when machining mild steel AISI 1018. This analysis helped to select the process parameters to improve machinability, which reduces cost and time of the turning process.

Surface Roughness Optimization of some Machining Parameters in Turning Operations Using Taguchi Method

2009 ◽  
Vol 62-64 ◽  
pp. 613-620 ◽  
Author(s):  
Ishaya Musa Dagwa
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Signal To Noise Ratio ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Confirmatory Test ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Turning Operations ◽  
Factors Affecting

In this study, an attempt has been made to optimize cutting parameters (cutting speed, depth of cut, and feed rate) in conventional turning operations. A Taguchi orthogonal array (L933) was used in surface roughness optimization of a solid round bar of mild steel material. The experimental runs were randomized; two skilled machinists were involved in the turning operation using the same machining parameters. ANOVA analysis was performed to identify the percentage contribution of the factors affecting surface roughness during machining. The optimal cutting combination was determined by using the signal-to-noise ratio and the following results were obtained; speed (level 2) = 55.m/min, depth of cut (level 3) = 0.08mm, and feed rate (levels 3) = at 0.08mm/rev. A prediction of surface roughness was carried out using the optimal setting followed by a confirmatory test on the lathe. The result shows that the confirmatory runs compared favourably (96.44%) with the predicted surface roughness.

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