Multi-objective optimization of machining parameters during green machining of aerospace grade titanium alloy using Grey–Taguchi approach

2021 ◽  
pp. 095440892110436
Author(s):  
Pawan Kumar ◽  
Pradeep K Karsh ◽  
Joy P Misra ◽  
Jatinder Kumar
Keyword(s):  
Titanium Alloy ◽  
Removal Rate ◽  
Cutting Speed ◽  
Machining Parameters ◽  
Taguchi Approach ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Process Characteristics ◽  
Wear Tool ◽  
Grey Taguchi

This paper presents multi-objective optimization of aerospace-grade titanium alloy using the Gray–Taguchi approach. Experimentation has been conducted with varying cutting conditions according to Taguchi's L9 orthogonal array. Tool nose wear, tool flank wear, surface roughness and material removal rate are employed as process characteristics. The experimental outcomes are statistically analyzed using the Grey–Taguchi approach. Statistical and sensitivity analysis are also performed. Studies revealed that cutting speed and feed rate are having a significant influence on process performances. Micro analysis of cutting tool is also performed to study the kind of wear. Furthermore, chips were also analysed using scanning electron microscope to study its features and morphology to obtain a better insight into the process.

Multi-Objective Optimization using Grey Relational Taguchi Analysis in Machining

2016 ◽  
Vol 6 (4) ◽  
pp. 45-64 ◽  
Author(s):  
Nirmal S. Kalsi ◽  
Rakesh Sehgal ◽  
Vishal S. Sharma
Keyword(s):  
Metal Cutting ◽  
Removal Rate ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Recent Approach ◽  
Grey Relational

Multi-objective optimization is becoming important day by day due to increase in complexity of the processes and expectations of more reliable solutions. In view of the complexity of the process, controlling the machining parameters without compromising on the response parameters is a tedious process. In the recent approach, researchers have used many combinations of available techniques to solve multi performance characteristic problems depending upon the situation and accuracy desired in the results, to make the results more reliable. In this paper, the authors have pronounced and used a combination of grey relational and Taguchi based analysis to optimize a multi-objective metal cutting process to yield maximum performance of cutting tools in turning. Main cutting force, power consumption, tool wear and material removal rate were evaluated used L18 orthogonal array considering cutting speed, feed rate and depth of cut, using cryogenically treated and untreated tungsten carbide cutting tool inserts.

MULTI-OBJECTIVE OPTIMIZATION OF TURNING PARAMETERS USING THE COMBINED MOORA AND ENTROPY METHOD

2016 ◽  
Vol 40 (1) ◽  
pp. 101-111 ◽  
Author(s):  
B. Singaravel ◽  
T. Selvaraj ◽  
S. Vinodh
Keyword(s):  
Removal Rate ◽  
Cutting Speed ◽  
Entropy Method ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Multi Objective Optimization ◽  
Nose Radius ◽  
Multi Objective ◽  
Entropy Measurement ◽  
Coated Carbide

Selection of optimum machining parameters in machining operations leads to good functional attributes for the machined components and increased productivity. In this work, machining parameters and nose radius are optimized in turning of EN25 steel with coated carbide tool by the application of combined Multi-Objective Optimization by Ratio Analysis (MOORA) and entropy measurement method. The selected machining parameters are cutting speed, feed rate, depth of cut and nose radius for minimization of surface roughness, micro-hardness and maximization of Material Removal Rate (MRR). Entropy concept has been used to assign the weight criteria of each objective being considered. The optimum combination of machining parameters and nose radius are obtained using normalized assessment values. The results obtained in the analysis are validated and the results based on turning process responses can be effectively improved.

Multi-Objective Optimization of Electrical Discharge Machining Parameters for 2024 Aluminum Alloy Using Grey-Taguchi Method

2020 ◽  
Vol 998 ◽  
pp. 55-60
Author(s):  
Jurapun Phimoolchat ◽  
Apiwat Muttamara
Keyword(s):  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Electrode Wear ◽  
Machining Parameters ◽  
Multi Objective Optimization ◽  
2024 Aluminum Alloy ◽  
Multi Objective ◽  
Effect Estimation ◽  
Voltage Performance ◽  
Pulse On Time

This paper focused on Grey relational analysis (GRA) to optimize EDM parameters through multi-objective optimization for Al2024 aluminum and electrode graphite ISO-63 was used as a cutting tool. The process parameters pulse on time, duty factor, pulse current and open voltage. Performance characteristics examined included material removal rate (MRR), electrode wear ratio (EWR) and surface roughness (SR). Taguchi’s 27 experimental designs, often called an orthogonal array (OA), was utilized to ignore interaction and concentrate on main effect estimation. GRA was performed to optimize input parameters levels. Results were that MRR increased from 35.00 to 35.11 mm3/min, EWR decreased from 11.63 to 10.89 mm3/min, and SR decreased from 5.01 to 4.97 μm. Taguchi and GRA resulted in clear improvements in MRR, EWR, and SR.

A Simple GA Based Approach for Multi-Objective Optimization of Machining Parameters

2014 ◽  
Vol 974 ◽  
pp. 402-407 ◽  
Author(s):  
Akhtar Waseem ◽  
Jian Fei Su ◽  
Wu Yi Chen ◽  
Peng Fei Sun
Keyword(s):  
Experimental Data ◽  
Genetic Algorithm ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Simple Approach ◽  
Machining Parameters ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Multi Objective

A simple approach to multi-objective optimization of machining parameters is presented. Regression analysis of experimental data is carried out to obtain the correlation between cutting parameters and response variables. Finally, Genetic Algorithm (GA) toolbox ofMATLABis used to carry out multi-objective optimization of two objective functions (surface roughness “Ra” & material removal rate “MRR”). Genetic algorithm is found to be a powerful tool for multi-objective optimization of machining parameters in this study.

scholarly journals Multi-Objective Optimization of Processing Parameters for Disc-Mill Cutter Machining Blisk-Tunnel Based on GRA-RBF-FA Method

2019 ◽  
Vol 37 (1) ◽  
pp. 160-166
Author(s):  
Nan Zhang ◽  
Yaoyao Shi ◽  
Chen Yang ◽  
Zhen Chen ◽  
Jiang Liu
Keyword(s):  
Removal Rate ◽  
Rbf Neural Network ◽  
Cutting Speed ◽  
Integrated Approach ◽  
Processing Parameters ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Mill Cutter ◽  
Cutting Height ◽  
Grey Relational

The process of disc-mill cutter machining blisk-tunnel is a typical multi-input and multi-output system, therefore multi-objective optimization is applied to improve the process. In this paper, an integrated approach that Grey Relational Analysis(GRA)couples with Radial Basis Function (RBF) neural network and Firefly algorithm (FA) is used to solve the optimization problem. The aim is to satisfy the minimum cutting force and maximum material removal rate simultaneously by optimizing the cutting speed, feed rate per tooth and cutting height. The results for verifying experiment indicated that GRA-RBF-FA method can be applied to optimize the processing parameters of disc-mill cutter machining TC17 blisk-tunnel and the optimization results are superior to the GRA's.

Performance Investigation of Powder Mixed Electro Discharge Machining of Hypoeutectic Al-Si Alloy Using Brass Electrode

2019 ◽  
Vol 6 (2) ◽  
pp. 31-43
Author(s):  
Baliram Rajaram Jadhav ◽  
M. S. Sohani ◽  
Shailesh Shirguppikar
Keyword(s):  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Input Parameter ◽  
Optimal Solution ◽  
Machining Parameters ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Pulse On Time ◽  
Taguchi’S Design Of Experiments ◽  
Grey Relation

The aim of this study is the multi- objective optimization of process parameters of Al- Si alloy in powder mixed electrical discharge machining for obtaining minimum surface roughness, minimum tool wear rate, and maximum material removal rate. The important machining parameters were selected as discharge current, voltage and pulse-on time. Experiments were conducted by selecting different operating levels for the three parameters according to Taguchi's Design of Experiments. The multi-objective optimization was performed using Grey Relation Analysis to determine the optimal solution. The Grey Relation Grade values were then analysed using analysis of variance to determine the most contributing input parameter. On analysis it was found that peak current, pulse-on time, and voltage had an influence of 94.73%, 3.32% and 0.36%, respectively, on the multi-performance characteristics.

Multi-Objective Optimization of CNC Turning Machining Parameters

2014 ◽  
Vol 1016 ◽  
pp. 172-176 ◽  
Author(s):  
Sharad Kumar Pradhan ◽  
Surendra Kumar Saini
Keyword(s):  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Multi Objective Optimization ◽  
Cnc Turning ◽  
Multi Objective ◽  
Machining Parameter

An experimental investigation into CNC turning operation on Brass C36000 alloy as work piece material which is widely used for various industrial applications is performed. Multi objective optimization is carried out to find out the influencing machining parameters among spindle speed (rpm), feed (mm per revolution) and depth of cut (mm) for CNC turning of Brass C36000 alloy with surface finish and Material Removal Rate as performance parameters using Taguchi method. Taguchi orthogonal array [L27(33)] is used for the experimental design. All experiments are conducted using EMCO Concept Turn 250 machine tool with carbide insert cutting tool. The optimization result shows that feed is the most significant turning machining parameter for surface roughness while depth of cut has high influence on material removal rate followed by spindle speed during CNC turning of Brass C36000 alloy. Above results is further validated using ANOVA approach.

scholarly journals Combining Taguchi method and DEAR method for multi-objective optimization of grinding process

2021 ◽  
Vol 309 ◽  
pp. 01220
Author(s):  
Do Duc Trung ◽  
Nguyen Huu Quang ◽  
Dang Quoc Cuong ◽  
Nguyen Hong Linh ◽  
Nguyen Van. Tuan ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Removal Rate ◽  
Cutting Speed ◽  
Grinding Process ◽  
Multi Objective Optimization ◽  
Pareto Chart ◽  
Multi Objective ◽  
Input Parameters ◽  
Experimental Process

In this paper, a study on multi-objective optimization of the cylindrical grinding process is presented. The experimental material used in this study is X12M steel. The two output parameters of the grinding process considered in this study are surface roughness and material removal rate (MRR). The cutting mode parameters including cutting speed, feed rate, and cutting depth have been selected as input parameters of the experimental process. Experimental matrix by Taguchi method has been used to design a matrix with 27 experiments. Analysis of experimental results by Pareto chart has determined the effect of input parameters on output parameters. The Data Envelopment Analysis-based Ranking (DEAR) method has been applied to determine the values of input parameters to simultaneously ensure the two criteria of minimum surface roughness and maximum MRR. Finally, the development direction for further studies has also been recommended in this study.

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