Multi-Response Optimization in Turning of AA6061 T6 Using Desirability Function Analysis

2015 ◽  
Vol 812 ◽  
pp. 124-129 ◽  
Author(s):  
P. Jayaraman ◽  
L. Mahesh Kumar
Keyword(s):  
Function Analysis ◽  
Removal Rate ◽  
Desirability Function ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Multiple Responses ◽  
Ideal Approach ◽  
Response Optimization ◽  
Desirability Function Analysis

This paper presents an ideal approach for the optimization of machining parameters on turning of AA6061 T6 aluminium alloy with multiple responses based on orthogonal array with desirability function analysis. In this study, turning parameters namely cutting speed, feed rate and depth of cut are optimized with the considerations of multiple responses such as surface roughness (Ra), roundness (Ø) and material removal rate (MRR). Multi response optimization of machining parameters was done through desirability function analysis. The optimum machining parameters have been identified by a composite desirability value obtained from desirability function analysis. The performance index and significant contribution of process parameters were determined by analysis of variance.

Optimization in Hot Turning of Nickel Based Alloy Using Desirability Function Analysis

2016 ◽  
Vol 24 ◽  
pp. 64-70 ◽  
Author(s):  
A.K. Parida ◽  
K.P. Maity
Keyword(s):  
Feed Rate ◽  
Function Analysis ◽  
Desirability Function ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Cutting Velocity ◽  
Nickel Based Alloy ◽  
Desirability Function Analysis ◽  
Hot Turning

This paper presents a desirability function approach in order to find out an optimal combination of Machining parameters for multi-response parameters in hot turning operation of nickel based alloy. Taguchi’s L9 orthogonal array is used for experimental design. The machining parameters such as cutting velocity, feed rate, depth of cut and temperature are optimized by multi-response considerations namely power, flank wear, and MRR. ANOVA test was carried out and it was found that cutting speed is most influence parameter followed by feed rate, depth of cut and workpiece temperature. The optimization of machining parameters was found at 5.8 m/min of cutting speed, 30 °C preheating temperature, 0.2 mm depth of cut and 0.15 mm/rev feed rate

scholarly journals Machinability Studies and Optimization of AA 6082/Fly Ash/Carbonized Eggshell Matrix Composite

2021 ◽  
Vol 31 (4) ◽  
pp. 207-216
Author(s):  
Ndudim H. Ononiwu ◽  
Chigbogu G. Ozoegwu ◽  
Nkosinathi Madushele ◽  
Esther T. Akinlabi
Keyword(s):  
Fly Ash ◽  
Function Analysis ◽  
Removal Rate ◽  
Desirability Function ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Chip Morphology ◽  
Influential Factor ◽  
Depth Of Cut ◽  
Desirability Function Analysis

Machinability studies of aluminium matrix composites (AMCs) is a necessary investigation required to understand their behaviour during machining to produce components effectively and efficiently. This established need has led to the investigation into the machinability of AA 6082 reinforced with 2.5 wt.% fly ash and 2.5 wt.% carbonized eggshell fabricated via stir casting. The studied machinability indices were material removal rate (MRR), cutting temperature, built-up edges (BUE) formation and chip morphology while the selected inputs were cutting speed (100 mm/min, 200 mm/min, 300 mm/min), feed (0.1 mm/rev, 0.2 mm/rev, 0.3 mm/rev) and depth of cut (0.5 mm, 1 mm, 1.5 mm). For the experimental design, the L9 orthogonal array was preferred to create 9 experimental runs. The analysis of the built-up edges showed that it increased at lower cutting speeds and increased feed and depth of cut. The examination of the produced chips after each experimental run showed the presence of c-shaped, helically shaped and ribbon-shaped chips. The analysis of variance (ANOVA) for both MRR and cutting temperature indicated that the depth of cut was the most influential factor on both responses. Multi-objective optimization using desirability function analysis showed that the optimum combination of parameters was 300 mm/min, 0.2 mm/rev and 1.0 mm for the cutting speed, feed and depth of cut respectively. The ANOVA of the composite desirability indicated that the cutting speed was the most contributing factor.

Optimization of Machining Hybrid Metal Matrix Composites Using Desirability Analysis

2014 ◽  
Vol 875-877 ◽  
pp. 1412-1420 ◽  
Author(s):  
R.R. Jai Preetham ◽  
Joel Morris ◽  
Kaushik Rajasekaran
Keyword(s):  
Tool Wear ◽  
Metal Matrix Composites ◽  
Metal Matrix ◽  
Function Analysis ◽  
Desirability Function ◽  
Cutting Speed ◽  
Machining Parameters ◽  
Matrix Composites ◽  
Hybrid Metal Matrix Composites ◽  
Desirability Function Analysis

This paper presents the detailed discussions on fabrication of Aluminium - silicon carbide (10% by weight of particles) and boron carbide (5% by weight of particles) Hybrid Metal Matrix Composites (Al/SiC/B4C MMC) using stir casting method. SiC and a B4C particle range from 30μm to 50 μm. The cylindrical rods of diameter 60 mm and length 250 mm are fabricated and subsequently machined using medium duty lathe of 2 kW spindle power to study the machinability issues of Hybrid MMC using Poly Crystalline Diamond (PCD) insert of 1600 grade. The optimum machining parameters have been identified by a composite desirability value obtained from desirability function analysis as the performance index, and significant contribution of parameters can then be determined by analysis of variance. Confirmation test is also conducted to validate the test result. Experimental results have shown that machining performance can be improved effectively through this approach. Results show at higher cutting speeds, good surface finish is obtained with faster tool wear. It is concluded that, tool wear and cutting force are directly proportional to the cutting speed, where as surface roughness is inversely proportional to the cutting speed. Percentage of error obtained between experimental value and predicted value is within the limit.

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.  

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.

Multi-criteria optimization and predictive modeling of turning forces in high-speed machining of yttria based zirconia toughened alumina insert using desirability function approach

2015 ◽  
Vol 231 (8) ◽  
pp. 1396-1408 ◽  
Author(s):  
Nilrudra Mandal ◽  
B Doloi ◽  
Biswanath Mondal ◽  
BK Singh
Keyword(s):  
Feed Rate ◽  
High Speed ◽  
Desirability Function ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Machining Forces ◽  
Feed Force ◽  
Response Optimization ◽  
Zirconia Toughened Alumina

An attempt has been made to apply the Taguchi parameter design method and multi-response optimization using desirability analysis for optimizing the cutting conditions (cutting speed, feed rate and depth of cut) on machining forces while finish turning of AISI 4340 steel using developed yttria based zirconia toughened alumina inserts. These zirconia toughened alumina inserts were prepared through wet chemical co-precipitation route followed by powder metallurgy process. The L9 (4) orthogonal array of the Taguchi experiment is selected for three major parameters, and based on the mean response and signal-to-noise ratio of measured machining forces, the optimal cutting condition arrived for feed force is A1, B1 and C3 (cutting speed: 150 m/min, depth of cut: 0.5 mm and feed rate: 0.28 mm/rev) and for thrust and cutting forces is A3, B1 and C1 (cutting speed: 350 m/min, depth of cut: 0.5 mm and feed rate: 0.18 mm/rev) considering the smaller-the-better approach. Multi-response optimization using desirability function has been applied to minimize each response, that is, machining forces, simultaneously by setting a goal of highest cutting speed and feed rate criteria. From this study, it can be concluded that the optimum parameters can be set at cutting speed of 350 m/min, depth of cut of 0.5 mm and feed rate of 0.25 mm/rev for minimizing the forces with 78% desirability level.

scholarly journals Prediction of Machining Characteristics of Hybrid Composites Using Response Surface Methodology Approach

2018 ◽  
Vol 7 (3.1) ◽  
pp. 162 ◽  
Author(s):  
Ramanan. G ◽  
Rajesh Prabha.N ◽  
Diju Samuel.G ◽  
Jai Aultrin. K. S ◽  
M Ramachandran
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Hybrid Composites ◽  
Removal Rate ◽  
Cutting Speed ◽  
Chemical Properties ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Optimal Parameters ◽  
Rsm Technique

This manuscript presents the influencing parameters of CNC turning conditions to get high removal rate and minimal response of surface roughness in turning of AA7075-TiC-MoS2 composite by response surface method. These composites are particularly suited for applications that require higher strength, dimensional stability and enhanced structural rigidity. Composite materials are engineered materials made from at least two or more constituent materials having different physical or chemical properties. In this work seventeen turning experiments were conducted using response surface methodology. The machining parameters cutting speed, feed rate, and depth of cut are varied with respect to different machining conditions for each run. The optimal parameters were predicted by RSM technique. Turning process is studied by response surface methodology design of experiment. The optimal parameters were predicted by RSM technique. The most influencing process parameter predicted from RSM techniques in cutting speed and depth of cut.   

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.

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