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.

Modelling and Optimization of Machining parameters for Turning Automotive Shafts using RSM and Grey Relational Analysis

2020 ◽  
Vol 12 (4) ◽  
Author(s):  
S. Dinesh ◽  
K. Rajaguru ◽  
K. Saravanan ◽  
R. Yokeswaran ◽  
V. Vijayan
Keyword(s):  
Surface Roughness ◽  
Grey Relational Analysis ◽  
Removal Rate ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Relational Analysis ◽  
Input Parameters ◽  
Grey Relational ◽  
Central Composite ◽  
Modelling And Optimization

Automotive shafts require maximum strength with regard to axial, bending and torsional loading to transmit power to various parts of a vehicle. Hence, it is very critical to analyse the manufacturing process and its governing parameters to exercise control over the surface properties of the shaft as it needs to be precisely manufactured in terms of dimensions and the surface roughness. The effect of three input parameters over two responses are considered as two major criteria's for production of shaft. The input parameters are speed, feed and depth of cut whereas the responses are material removal rate and surface roughness. Central Composite design was used and experimental results were analysed with Response Surface Methodology. ANOVA analysis was carried out to identify the most contributing parameter for MRR and SR. Grey Relational Analysis was adopted to identify the most feasible combination of machining parameters for turning process. The optimized parameter is identified as speed of 1000 rpm, 0.15 mm of feed and 0.35 mm of depth of cut using Grey Relational Analysis.

EFFECT OF MACHINING PARAMETERS ON SURFACE ROUGHNESS FOR ALUMINIUM MATRIX COMPOSITE BY USING TAGUCHI METHOD WITH DECISION TREE ALGORITHM

2021 ◽  
pp. 2150021
Author(s):  
P. RAVEENDRAN ◽  
S. V. ALAGARSAMY ◽  
M. RAVICHANDRAN ◽  
M. MEIGNANAMOORTHY
Keyword(s):  
Surface Roughness ◽  
Decision Tree ◽  
Taguchi Method ◽  
Cutting Speed ◽  
Experimental Result ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Cnc Turning ◽  
Cnc Turning Process ◽  
Taguchi’S Design Of Experiments

The intend of this research work is to explore the effect of various parameters in a CNC turning process like cutting speed ([Formula: see text]), feed ([Formula: see text]), and depth of cut ([Formula: see text]) on surface roughness (Ra) of turning AA7075 filled with 10[Formula: see text]wt.% of TiO2 composite fabricated through stir casting method. Taguchi method and decision tree (DT) algorithm were utilized to foresee the surface roughness (Ra) of the proposed composite. The microstructure of composite was ensured with the presence of TiO2 particles dispersed in a homogeneous manner within the matrix material. The machining of composite was carried out by using the CNC turning center and tungsten carbide insert as tool material. This experimental work was designed on L27 (33) orthogonal array using Taguchi’s design of experiments. From its signal-to-noise (S/N) ratio study, the minimum surface roughness (Ra) was obtained at the optimum level of parameters with the cutting speed at 1500[Formula: see text]rpm, feed at 0.15[Formula: see text]mm/rev and depth of cut at 0.3[Formula: see text]mm. Analysis of variance (ANOVA) and decision tree (DT) algorithm were used to identify the significant effect of parameters. The experimental result shows that depth of cut was the major significant parameter on surface roughness (Ra) when compared to cutting speed and feed.

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.

scholarly journals Optimization Of Machining Process Parameters In Turning And Drilling By using Design Of Experiments With Aluminum 6061-O Alloy And Austenitic Stainless Steel

2019 ◽  
Vol 8 (11) ◽  
pp. 625-633
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Design Of Experiments ◽  
Process Parameters ◽  
Removal Rate ◽  
Cutting Speed ◽  
Machining Process ◽  
Depth Of Cut ◽  
Drilling Operation ◽  
Input Parameters

Optimization is required everywhere particularly in the industrial sector. As a part of that machining emphasized in this paper to optimize the parameters involved in the turning and drilling operation on CNC machines using the Aluminum and Stainless steel alloys. The task is initiated with design of experiments and hence the cost of operation is also reduced. During the experimental process the input parameters involved for turning were considered as cutting speed, feed and depth of cut. And for the drilling operation the input process parameters considered were speed of drill, feed. The output parameters emphasized were surface roughness and dimensional accuracy. By the investigation using the experiments, it in turn leads to an optimized environment for the operation that was carried out. Taguchi technique is a widely used and efficient technique for correlating the process parameters for an efficient and effective operation. Then the process L9 and L16 orthogonal arrays were chosen and signal to noise ratios were computed. At the end the input parameters speed, feed, depth of cut, depth of drill and outcome parameters surface roughness, material removal rate and time of operation were optimized.

scholarly journals Review on optimization of CNC Turning Process Parameters for Surface Roughness and Material Removal Rate Using Taguchi, GRA, and RSM Approaches

2021 ◽  
Vol 23 (3) ◽  
Author(s):  
Neeraj A ◽  
◽  
Sukhdeep S. Dhami ◽  
Keyword(s):  
Process Parameters ◽  
Metal Cutting ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Cnc Turning ◽  
Current Trends ◽  
Grey Relational ◽  
The Impact ◽  
Cnc Turning Process

Nowadays, the realization of a fine surface finish is the main objective of the metal cutting industry during the turning processes.This work consists of an analysis of the work carried out by the researchers in the field of filming process parameters, to Examine the impact of speed, cutting speed (feed), and depth of cut in a computer numeric control machine. This study will provide insight into current trends research in the area of Taguchi, Grey Relational Analysis, Response Surface Method, ANOVA & CNC Turning.

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.

scholarly journals Multiresponse Optimization of Process Parameters in Turning of GFRP Using TOPSIS Method

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Arun Kumar Parida ◽  
Bharat Chandra Routara
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Optimal Process ◽  
Level 3 ◽  
Level 1

Taguchi’s design of experiment is utilized to optimize the process parameters in turning operation with dry environment. Three parameters, cutting speed (v), feed (f), and depth of cut (d), with three different levels are taken for the responses like material removal rate (MRR) and surface roughness (Ra). The machining is conducted with Taguchi L9 orthogonal array, and based on the S/N analysis, the optimal process parameters for surface roughness and MRR are calculated separately. Considering the larger-the-better approach, optimal process parameters for material removal rate are cutting speed at level 3, feed at level 2, and depth of cut at level 3, that is, v3-f2-d3. Similarly for surface roughness, considering smaller-the-better approach, the optimal process parameters are cutting speed at level 1, feed at level 1, and depth of cut at level 3, that is, v1-f1-d3. Results of the main effects plot indicate that depth of cut is the most influencing parameter for MRR but cutting speed is the most influencing parameter for surface roughness and feed is found to be the least influencing parameter for both the responses. The confirmation test is conducted for both MRR and surface roughness separately. Finally, an attempt has been made to optimize the multiresponses using technique for order preference by similarity to ideal solution (TOPSIS) with Taguchi approach.

scholarly journals Fuzzy-MOORA Based Optimization of Machining Parameters for Machinability Enhancement of Titanium

2021 ◽  
Vol 8 (2) ◽  
pp. 189-198
Author(s):  
Durwesh Jhodkar ◽  
Akhtar Khan ◽  
Kapil Gupta
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Process Parameters ◽  
Flank Wear ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Tool Flank Wear ◽  
Moora Method ◽  
Fuzzy Moora

The aim of this study is to determine the optimal combination of process parameters when machining commercially pure titanium grade 2. The unification of Multi objective optimization based on ratio analysis (MOORA) and fuzzy approach has applied to optimize the process parameters. Three process parameters i.e. cutting speed, tool overhang, and microhardness have been varied at three levels each and a total of twenty seven experiments have been conducted based on Taguchi’s L27 design of experiment technique. Cutting force, tool flank wear, and average surface roughness have been considered a machinability indicators to measure the process performance. Feed rate and depth of cut have been kept constant. Successful optimization is done and results show that machining titanium at higher cutting speed (140 m/min) and higher tool overhang length (65 mm) with medium hardness (1934 HV) results in lower cutting force, tool flank wear, and surface roughness. Outcomes of the present work reveal that the hybrid fuzzy-MOORA method is convincing enough to obtain the best process parameter combination for the best machinability while machining titanium type difficult-to-machine materials.

Application of Taguchi’s Method for Study of Machining Parameters on Surface Roughness of 7136 Aluminum Alloy in End Milling

2015 ◽  
Vol 809-810 ◽  
pp. 123-128 ◽  
Author(s):  
Alina Bianca Bonţiu Pop
Keyword(s):  
Surface Roughness ◽  
Aluminum Alloy ◽  
Process Parameters ◽  
End Milling ◽  
Signal To Noise Ratio ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Future Research ◽  
Depth Of Cut ◽  
Machining Parameters

Starting with the necessity to identify the optimum values of the cutting parameters which are affecting the surface quality, it is appropriate to use the design of experiment techniques to conduct the experiments. Previous researches [1] focused on the investigation of the effects of machining parameters on surface roughness. In this paper, the experiments were conducted based on the established Taguchi’s technique, L8 orthogonal array using Minitab-17 statistical software. Three machining parameters are chosen as process parameters: Cutting Speed, Feed per tooth and Depth of cut. The orthogonal matrix includes these three factors set for analysis, each with 2 levels associated. The level of influence that the process parameters exert on the surface roughness is analyzed by Taguchi method data analysis. In this case the signal to noise ratio was tacked into account. Also, the recommended configuration regarding the optimum values of these parameters was determined as well as the interactions between them, in order to obtain better surface roughness for 7136 aluminum alloy machining. The final results will be used as data for future research.

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