scholarly journals Multi Response Optimization of Process Parameters during Machining of Aluminium by Satisfaction Function

2019 ◽  
Vol 8 (3) ◽  
pp. 8591-8596
Keyword(s):  
Process Parameters ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Satisfaction Function ◽  
Performance Factors ◽  
Optimization Of Process Parameters ◽  
Lathe Machine ◽  
Response Optimization ◽  
Manufacturing Environments

Economical machining operation plays an important part in competitiveness in the industries therefore selection of optimum cutting parameters is of great concern in manufacturing environments. The current research is aimed at fixing the optimal process parameters for hard turning of aluminum in CNC lathe machine using carbide tool as per the machinability aspects. On the basis of three-factor-three-level L9 orthogonal array, trials are performed by varying the manageable process constraints which are spindle speed, depth of cut and feed rate. Performance of machining has been figured by several responses like Surface Roughness and Material Removal Rate. Towards optimization above mentioned performance factors are treated as purpose functions, assuming that it corresponds to Higher-is-better and Lower-is-Better requirement respectively. Satisfaction function approach is used in this paper to find out satisfactions of individual responses enabling gathering of multi-responses into a comparable sole index

Optimization of Process Parameters Using Taguchi Coupled Genetic Algorithm

2017 ◽  
pp. 67-93 ◽  
Author(s):  
Supriyo Roy ◽  
J. Paulo Davim ◽  
Kaushik Kumar
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Machining Process ◽  
Depth Of Cut ◽  
Nsga Ii ◽  
Optimization Of Process Parameters ◽  
Cnc Lathe

In the era of mass manufacturing, Material removal rate and Surface Roughness are of primary concern even in manufacturing using contemporary CNC machines. In this work, L27 Orthogonal Array of Taguchi method is selected for three parameters (Depth of cut, Feed and Speed) with three different levels to optimize the turning parameters for Material Removal Rate and Surface Roughness on an EMCO Concept Turn 105 CNC lathe for machining SAE 1020 material with carbide tool. The MRR and SR are observed as the objective to develop the combination of optimum cutting parameters. The objectives were optimized using Taguchi, Grey Taguchi and NSGA-II. The result from these techniques was compared to identify the optimal values of cutting parameters for maximum MRR, minimum SR and best combination of both. This study also produced a predictive equation for determining MRR and SR for a given set of parameters outside the considered values. Thus, with the proposed optimal parameters it is possible to increase the efficiency of machining process and decrease production cost in CNC Lathe.

Optimization of Cutting Parameters in Milling Process Using Genetic Algorithm and ANOVA (March 2020)

2020 ◽  
Vol 38 (10A) ◽  
pp. 1489-1503
Author(s):  
Marwa Q. Ibraheem
Keyword(s):  
Genetic Algorithm ◽  
Tool Wear ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Optimal Value ◽  
Optimization Of Cutting Parameters

In this present work use a genetic algorithm for the selection of cutting conditions in milling operation such as cutting speed, feed and depth of cut to investigate the optimal value and the effects of it on the material removal rate and tool wear. The material selected for this work was Ti-6Al-4V Alloy using H13A carbide as a cutting tool. Two objective functions have been adopted gives minimum tool wear and maximum material removal rate that is simultaneously optimized. Finally, it does conclude from the results that the optimal value of cutting speed is (1992.601m/min), depth of cut is (1.55mm) and feed is (148.203mm/rev) for the present work.

Micro Textured Cutting Inserts with Solid Lubrication as Alternative Coolant to Mineral Oil-Based Cutting Fluid in Turning Operation

2021 ◽  
Vol 13 (4) ◽  
Author(s):  
C. Divya ◽  
L. Suvarna Raju ◽  
B. Singaravel
Keyword(s):  
Process Parameters ◽  
Orthogonal Array ◽  
Inconel 718 ◽  
Cutting Speed ◽  
Solid Lubricants ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Turning Process ◽  
Optimization Of Process Parameters ◽  
Cutting Inserts

Turning process is a primary process in engineering industries and optimization of process parameters enhance the machining performance. Inconel 718 is a nickel-based superalloy, widely found applications in the manufacturing of blades, sheets and discs in aircraft engines and rocket engines. It provides toughness at low temperature, with stand high mechanical stresses at elevated temperature and creep resistance. In this work, turning process is carried out on Inconel 718 with micro whole textured cutting inserts filled with solid lubricants. Three different solid lubricants are used namely molybdenum-di-sulfide (MoS2), tungsten-di-sulfide (WS2) and calcium-di-fluoride (CaF2). Experiments are performed as per L9 orthogonal array. Statistical approaches such as orthogonal array, Signal-to-Noise (S/N) ratio and Analysis of Variance (ANOVA) are used to find the importance and effects of machining parameters. In this study, input parameters included are feed, cutting speed and depth of cut and output parameter includes surface roughness. Optimization of process parameters is carried out and the significance is estimated. The result suggested that WS2 followed by MoS2 and CaF2 given good surface finish value. Also, solid lubricant in machining enhances the sustainability in manufacturing.

Evaluation of Process Parameters in Machining of AA6063 Alloy

2018 ◽  
Vol 1148 ◽  
pp. 109-114
Author(s):  
M. Balaji ◽  
C.H. Nagaraju ◽  
V.U.S. Vara Prasad ◽  
R. Kalyani ◽  
B. Avinash
Keyword(s):  
Surface Roughness ◽  
Regression Analysis ◽  
Process Parameters ◽  
Single Channel ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Roughness Parameters ◽  
Surface Roughness Parameters ◽  
Aa6063 Alloy

The main aim of this work is to analyse the significance of cutting parameters on surface roughness and spindle vibrations while machining the AA6063 alloy. The turning experiments were carried out on a CNC lathe with a constant spindle speed of 1000rpm using carbide tool inserts coated with Tic. The cutting speed, feed rate and depth of cut are chosen as process parameters whose values are varied in between 73.51m/min to 94.24m/min, 0.02 to 0.04 mm/rev and 0.25 to 0.45 mm respectively. For each experiment, the surface roughness parameters and the amplitude plots have been noted for analysis. The output data include surface roughness parameters (Ra,Rq,Rz) measured using Talysurf and vibration parameter as vibration amplitude (mm/sec) at the front end of the spindle in transverse direction using single channel spectrum analyzer (FFT).With the collected data Regression analysis is also performed for finding the optimum parameters. The results show that significant variation of surface irregularities and vibration amplitudes were observed with cutting speed and feed. The optimum cutting speed and feed from the regression analysis were 77.0697m/min and 0.0253mm/rev. for the minimum output parameters. No significant effect of depth of cut on output parameters is identified.

scholarly journals Multi Performance Optimizationof Shoulder Milling Process Parameters of AA6063 T6 Aluminium Alloy by Taguchi Based GRA

2019 ◽  
Vol 8 (10S) ◽  
pp. 420-425
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Removal Rate ◽  
Analysis Data ◽  
Milling Process ◽  
Depth Of Cut ◽  
Analysis Method ◽  
Relational Analysis ◽  
Grey Relational Grade ◽  
Grey Relational

In this paper, a grey relational analysis method based on Taguchi is proposed to improve the multi-performance characteristics of VMC shoulder milling process parameters in the processing of AA6063 T6. Taking into account four process parameters such as coolant, depth of cut,speed and feed, there are three level of each process parameter in addition to two levels of coolant. 18 experiments were used by L18 orthogonal array using the taguchi method. Multi-performance features like surface roughness and material removal rate are used. Grey Relational Analysis method is used to obtain the Grey Relational Grade, and the multiperformance characteristics of the process are pointed out. Then, the Taguchi response table method and ANOVA are used to analysis data. In order to ensure the validity of the test results, a confirmation test was conducted. The study also shows that this method can effectively improve the multi-function characteristics of shoulder milling process.In his work microstructure and mechanical properties of AA6063 T6before and after shoulder milling have been investigated.

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