scholarly journals EFFECT OF MACHINING PARAMETERS ON SURFACE ROUGHNESS, POWER CONSUMPTION, AND MATERIAL REMOVAL RATE OF ALUMINIUM 6065-SI-MWCNT METAL MATRIX COMPOSITE IN TURNING OPERATIONS

2021 ◽  
Vol 22 (2) ◽  
pp. 283-293
Author(s):  
Savina Jaddinagadhe Puttaswamy ◽  
Raghavendra Bommanahalli Venkatagiriyappa
Keyword(s):  
Surface Roughness ◽  
Metal Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Stir Casting ◽  
Influential Factor ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Lathe Machine ◽  
Tungsten Carbide Tool

Nanocomposites were prepared with Al-6065-Si and multi walled carbon nanotubes of 1 wt.% as reinforcement through the stir-casting method. Fabricated nanocomposites were machined on a lathe machine using a tungsten carbide tool. The study investigated the multi-objective optimization of the turning operation. Cutting velocity, feed, and depth of cut were considered for providing minimum Surface Roughness of the workpiece. Also, the power consumed by the lathe machine with maximum metal removal rate was examined by surface response methodology. The design of experiments was developed based on rotational central composite design. Analysis of variance was executed to investigate the adequacy and the suitable fit of the developed mathematical models. Multiple regression models were used to represent the relationship between the input and the desired output variables. The analysis indicates that the feed is the most influential factor that effects the surface roughness of the workpiece. Cutting speed and the depth of cut are two other important factors that proportionally influence the power consumed by the lathe tool as compared to the feed rate. ABSTRAK: Komposit nano disediakan bersama Al-6065-Si dan karbon nanotiub berbilang dinding sebanyak 1 wt.% sebagai bahan penguat melalui kaedah kacauan-tuangan. Komposit nano yang terhasil melalui mesin pelarik ini menggunakan alat tungsten karbida. Kajian ini merupakan pengoptimuman pelbagai objektif operasi pusingan. Kelajuan potongan, suapan dan kedalaman potongan diambil kira sebagai pemberian minimum pada kekasaran permukaan bahan kerja. Tenaga yang digunakan bagi mesin pelarik dengan kadar maksimum penyingkiran logam diteliti melalui kaedah tindak balas permukaan. Rekaan eksperimen yang dibangunkan ini adalah berdasarkan rekaan komposit pusingan tengah. Analisis varian telah dijalankan bagi mengkaji kecukupan dan penyesuaian lengkap bagi model matematik yang dibangunkan. Model regresi berganda digunakan bagi menunjukkan hubungan antara input dan pembolehubah output yang dikehendaki. Analisis menunjukkan pemberian suapan merupakan faktor mempengaruhi keberkesanan kekasaran permukaan bahan kerja. Kelajuan pemotongan dan kedalaman potongan adalah dua faktor penting lain yang mempengaruhi kadar langsung ke atas tenaga yang digunakan oleh mesin pelarik dibandingkan kadar pemberian suapan.

Multiresponse Optimization of Al Alloy-SiC Composite Machining Parameters for Minimum Tool Wear and Maximum Metal Removal Rate

2013 ◽  
Vol 135 (2) ◽  
Author(s):  
Rajesh Kumar Bhushan
Keyword(s):  
Tool Wear ◽  
Metal Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Al Alloy ◽  
Machining Parameters ◽  
Metal Removal Rate ◽  
Nose Radius ◽  
Multiresponse Optimization

Optimization in turning means determination of the optimal set of the machining parameters to satisfy the objectives within the operational constraints. These objectives may be the minimum tool wear, the maximum metal removal rate (MRR), or any weighted combination of both. The main machining parameters which are considered as variables of the optimization are the cutting speed, feed rate, depth of cut, and nose radius. The optimum set of these four input parameters is determined for a particular job-tool combination of 7075Al alloy-15 wt. % SiC (20–40 μm) composite and tungsten carbide tool during a single-pass turning which minimizes the tool wear and maximizes the metal removal rate. The regression models, developed for the minimum tool wear and the maximum MRR were used for finding the multiresponse optimization solutions. To obtain a trade-off between the tool wear and MRR the, a method for simultaneous optimization of the multiple responses based on an overall desirability function was used. The research deals with the optimization of multiple surface roughness parameters along with MRR in search of an optimal parametric combination (favorable process environment) capable of producing desired surface quality of the turned product in a relatively lesser time (enhancement in productivity). The multi-objective optimization resulted in a cutting speed of 210 m/min, a feed of 0.16 mm/rev, a depth of cut of 0.42 mm, and a nose radius of 0.40 mm. These machining conditions are expected to respond with the minimum tool wear and maximum the MRR, which correspond to a satisfactory overall desirability.

Optimization of MRR and Surface Roughness of AlMg3 (AA5754) Alloy in CNC Lathe Machine by Using Taguchi Method

2018 ◽  
Vol 877 ◽  
pp. 110-117 ◽  
Author(s):  
Poornesh Kumar Chaturvedi ◽  
Harendra Kumar Narang ◽  
Atul Kumar Sahu
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Metal Removal ◽  
Removal Rate ◽  
Surface Condition ◽  
Point Of View ◽  
Depth Of Cut ◽  
Metal Removal Rate ◽  
Cnc Lathe ◽  
Lathe Machine

Quality of the product is the major concern in manufacturing industries from customers as well as producers point of view. There are number of factors in the product such as surface condition, height, weight, length, width etc., which may be consider for the measurement of the quality. Surface roughness and Metal Removal Rate (MRR) are the two main outcomes on which numerous researchers have applied different approaches for several years to get optimum results. In this study, Taguchi Method is applied for getting optimum parameters settings for Surface roughness and Metal Removal Rate (MRR) in case of turning AlMg3 (AA5754) in CNC Lathe machine, which is an aluminum alloy having diameter 20 mm and length 100 mm. The three parameters i.e. spindle speed, feed rate and depth of cut with 3 levels are taken as the process variables and the working ranges of these parameters for conducting experiments are selected based on Taguchi’s L9 Orthogonal Array (OA) design. To analyze the significant process parameters; main effect plots for data means and for S/N ratio are generated using Minitab statistical software.

scholarly journals Optimization of CNC Turning Parameters in Machining EN19 using Face Centered Central Composite Design Based RSM

2020 ◽  
Vol 9 (2) ◽  
pp. 889-896
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Removal Rate ◽  
Cutting Speed ◽  
Vital Role ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Cnc Turning ◽  
Software Analysis ◽  
Central Composite

Manufacturing a defect free (quality) product is playing a vital role in today’s globally competitive, customer oriented era. Meeting the demand of the market by producing sufficient quantity is another challenge. Achieving greater production rates without compromising on quality, increases the complexity of the task. Adopting modern manufacturing methods like CNC turning are essential to meet the above requirements. EN19 is an important member in the family of alloy steels, which has a wide variety of applications in automobile and machine tool industries. Optimization of machining parameters is crucial in obtaining the required outputs such as quality and productivity. In this work, optimization of CNC turning parameters for machining EN19 alloy steel is performed. The number of experiments was designed using face centred central composite based response surface methodology with varied independent process parameters namely cutting speed, feed and depth of cut. After designing the experiments, the performance measures such as surface roughness of the test samples and Material Removal Rate (MRR) is calculated using the existing formulae. The influence of parameters on MRR and surface roughness are determined by analysis of variance (ANOVA) and for significance interactions of the process parameters are also considered. Using MINITAB 17 software analysis is performed. Further, regression analysis has been done and second order mathematical model is obtained. Using desirability approach, optimization is carried out.

Optimization of tungsten carbide processing parameters for laser heating and ultrasonic vibration composite assisted cutting

2018 ◽  
Vol 233 (12) ◽  
pp. 4140-4153
Author(s):  
Feng Jiao ◽  
Ming-jun Zhang ◽  
Ying Niu
Keyword(s):  
Surface Roughness ◽  
Tungsten Carbide ◽  
Ultrasonic Vibration ◽  
Laser Heating ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Machining Properties

Laser heating assisted cutting is a lucrative technique for machining difficult-to-machine materials such as tungsten carbide (YG20), which uses a high power laser to focally heat a workpiece before the material removal with traditional or innovative cutting tool. In the latter case, the application of ultrasonic vibration to the cutting edge was found to replace the continuous cutting mode to the interrupted one, it reduces the adhesion and entanglement of chips, improves the tool wear and surface roughness of the workpiece. The combination of laser heating assisted cutting and two-dimensional ultrasonic vibration cutting methods has been successfully applied by the authors of this paper for cutting of tungsten carbide (YG20). In this follow-up study, the proposed composite method is experimentally and theoretically verified. Through the mathematical model and simulation analysis, its advantages, including small cutting force, softening the effect and improved machining properties of the processed material (YG20) are corroborated. The dependencies between the laser power, cutting speed, depth of cut, and feed rate on the surface roughness are established via the response surface methodology. The genetic algorithm is applied to the optimization of machining parameters by setting the material removal rate as the object variable and surface roughness as a constraint variable. The results obtained strongly suggest that the optimized parameters improve the processing efficiency and furnish the required processing quality.

Surface Roughness Prediction in End Milling of Machinable Glass Ceramic and Optimization by Response Surface Methodology

2011 ◽  
Vol 189-193 ◽  
pp. 1376-1381
Author(s):  
Moola Mohan Reddy ◽  
Alexander Gorin ◽  
Khaled A. Abou El Hossein
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Glass Ceramic ◽  
End Milling ◽  
Removal Rate ◽  
Cutting Speed ◽  
Lower Surface ◽  
Depth Of Cut ◽  
Machining Parameters

This paper presents the prediction of a statistically analyzed model for the surface roughness,R_a of end-milled Machinable glass ceramic (MGC). Response Surface Methodology (RSM) is used to construct the models based on 3-factorial Box-Behnken Design (BBD). It is found that cutting speed is the most significant factor contributing to the surface roughness value followed by the depth of cut and feed rate. The surface roughness value decreases for higher cutting speed along with lower feed and depth of cut. Additionally, the process optimization has also been done in terms of material removal rate (MRR) to the model’s response. Ideal combinations of machining parameters are then suggested for common goal to achieve lower surface roughness value and higher MRR.

Optimization of input machining parameters in SBCNC-60 for turning and drilling on P8 (H-13,HSS) material

2021 ◽  
Vol 58 (2) ◽  
pp. 640-663
Author(s):  
Arti Saxena ◽  
YM Dubey ◽  
Manish Kumar ◽  
Abneesh Saxena
Keyword(s):  
Taguchi Method ◽  
Metal Cutting ◽  
Metal Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Control Factor ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Cnc Machine ◽  
Input Control

Today’s technology of automobile manufacturing industries depends mainly on a metal cutting operation like turning and drilling. This paper aims to improve turning and drilling operations in industries where necessity is to increase productivity by improving the metal removal rate. This paper-work uses the Taguchi method to analyze the input control parameter and optimize the significant ones to obtain the desired output. Taguchi method is a broadly used technique for experimental design and analysis of experimental data to improve the performance of machining operations like face turning, drilling, etc. in a CNC machine by taking input control factor cutting speed (CS), feed rate (FR), depth of cut (DOC) and then find out the significant ones to optimize machining operation. In this paper, CNMG190616-M5-TM2501 and SD205A-1050–056-12R1-P cutting tool are used for turning and drilling operation respectively for H-13 (P8) material, and then by applying Taguchi L9 array and further analysis using ANOVA and validation test through regression model is done on input control parameters to obtain better optimum performance of SBCNC 60 lathe machine.

scholarly journals Dry turning of X2CrNi18-09 using coated carbide tools: modelling and optimization of multiple performance characteristics

Mechanika ◽  
2019 ◽  
Vol 25 (6) ◽  
pp. 487-500
Author(s):  
Septi Boucherit ◽  
Sofiane Berkani ◽  
Mohamed Athmane Yallese ◽  
Abdelkrim Haddad ◽  
Salim Belhadi
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Feed Rate ◽  
Removal Rate ◽  
Desirability Function ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Work Piece ◽  
Machining Parameters ◽  
Coated Carbide

The present paper investigates the cutting parameters pertaining to the turning of X2CrNi18-09 austenitic stainless steel that are studied and optimized using both RSM and desirability approaches. The cutting tool inserts used are the CVD coated carbide. The cutting speed, the feed rate and the depth of cut represent the main machining parameters considered. Their influence on the surface roughness and the cutting force are further investigated using the ANOVA method. The results obtained lead to conclude that the feed rate is the surface roughness highest influencing parameter with a contribution of 89.69%.The depth of cut and the feed rate are further identified as the most important parameters affecting the cutting force with contributions of 46.46% and 39.04% respectively. The quadratic mathematical models presenting the progression of the surface roughness and the cutting force and based on the machining parameters considered (cutting speed, feed rate and depth of cut) were obtained through the application of the RSM method. They are presented and compared to the experimental results. Good agreement is found between the two sections of the investigation. Furthermore, the flank wear of the CVD-coated carbide tool (GC2015) is found to increase with both cutting speed and cutting time. A higher tool life represented by t=44min is observed at cutting speed, feed rate and depth of cut of 280m/min,0.08mm/rev and 0.2mm respectively. Moreover and at low cutting speeds, the formation of micro weld is noticed and leads to an alteration of the surface roughness of the work piece. Finally, optimizing the machining parameters with the objective of achieving an improved surface roughness was accomplished through the application of the Desirability Function approach. This enabled to finding out the optimal parameters for maximal material removal rate and best surface quality for a cutting speed of 350m/min, a feed rate of 0.088 mm/rev and a depth of cut of 0.9mm.  

Effects of Process Parameters on Surface Roughness and MRR in the hard turning of EN 36 steel

2018 ◽  
pp. 102-110
Author(s):  
Amritpal Singh ◽  
Rakesh Kumar
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Material Removal ◽  
Hard Turning ◽  
Control Parameter ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Dry Cutting

In the present study, Experimental investigation of the effects of various cutting parameters on the response parameters in the hard turning of EN36 steel under the dry cutting condition is done. The input control parameters selected for the present work was the cutting speed, feed and depth of cut. The objective of the present work is to minimize the surface roughness to obtain better surface finish and maximization of material removal rate for better productivity. The design of experiments was done with the help of Taguchi L9 orthogonal array. Analysis of variance (ANOVA) was used to find out the significance of the input parameters on the response parameters. Percentage contribution for each control parameter was calculated using ANOVA with 95 % confidence value. From results, it was observed that feed is the most significant factor for surface roughness and the depth of cut is the most significant control parameter for Material removal rate.

Quantification of tool chatter and metal removal rate using wavelet denoising and statistical approach

2018 ◽  
Vol 49 (2) ◽  
pp. 62-81 ◽  
Author(s):  
Shailendra Kumar ◽  
Bhagat Singh
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Metal Removal ◽  
Removal Rate ◽  
Statistical Significance ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Metal Removal Rate ◽  
Chatter Index ◽  
Tool Chatter

Tool chatter is an unavoidable phenomenon encountered in machining processes. Acquired raw chatter signals are contaminated with various types of ambient noises. Signal processing is an efficient technique to explore chatter as it eliminates unwanted background noise present in the raw signal. In this study, experimentally recorded raw chatter signals have been denoised using wavelet transform in order to eliminate the unwanted noise inclusions. Moreover, effect of machining parameters such as depth of cut ( d), feed rate ( f) and spindle speed ( N) on chatter severity and metal removal rate has been ascertained experimentally. Furthermore, in order to quantify the chatter severity, a new parameter called chatter index has been evaluated considering aforesaid denoised signals. A set of 15 experimental runs have been performed using Box–Behnken design of experiment. These experimental observations have been used to develop mathematical models for chatter index and metal removal rate considering response surface methodology. In order to check the statistical significance of control parameters, analysis of variance has been performed. Furthermore, more experiments are conducted and these results are compared with the theoretical ones in order to validate the developed response surface methodology model.

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.

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