Multi-Objective Optimization using Grey Relational Taguchi Analysis in Machining

Author(s):  
Nirmal S. Kalsi ◽  
Rakesh Sehgal ◽  
Vishal S. Sharma

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.

2016 ◽  
Vol 40 (1) ◽  
pp. 101-111 ◽  
Author(s):  
B. Singaravel ◽  
T. Selvaraj ◽  
S. Vinodh

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.


Author(s):  
Nirmal S Kalsi ◽  
Rakesh Sehgal ◽  
Vishal S. Sharma

Due to the increase in complexity and expectations of more reliable solutions for a problem, the importance of multi-objective problem solutions is increasing day by day. It can play a significant role in making a decision. In the present approach, many combinations of the optimization techniques are proposed by the researchers. These hybrid evolutionary methods integrate positive characteristics of different methods and show the advantage to reach global optimization. In this chapter, Taguchi method and the GRA (Grey Relation Analysis) technique are pronounced and used to optimize a multi-objective metal cutting process to yield maximum performance of tungsten carbide-cobalt cutting tool inserts in turning. L18 orthogonal array is selected to analyze the effect of cutting speed, feed rate, and depth of cut using cryogenically treated and untreated inserts. The performance is evaluated in terms of main cutting force, power consumption, tool wear, and material removal rate using main effect plots of S/N (Signal to Noise) ratios. This chapter indicates that the grey-based Taguchi technique is not only a novel, efficient, and reliable method of optimization, but also contributes to satisfactory solution for multi-machining objectives in the turning process. It is concluded that cryogenically treated cutting tool inserts perform better. However, the feed rate affects the process performance most significantly.


2014 ◽  
Vol 592-594 ◽  
pp. 584-590 ◽  
Author(s):  
Vinay Varghese ◽  
K. Annamalai ◽  
K. Santhosh Kumar

This study investigates about machining practices used worldwide for machining of Inconel 718 super alloy. The effect of machining parameters like cutting speed, feed and depth of cut on machining responses like surface roughness and material removal rate when end milling Inconel 718 is studied using nine trials carried out based on L9 orthogonal array. A Taguchi based grey relational analysis was used for optimisation of machining parameters for high feed end milling operation on Inconel 718. An analysis of variance (ANOVA) was used to find the most significant factor. Validation of results through confirmation tests was performed and experimental results show that surface quality and productivity can be improved efficiently with this approach.


Author(s):  
Neeraj A ◽  
◽  
Sukhdeep S. Dhami ◽  

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.


Author(s):  
Pawan Kumar ◽  
Pradeep K Karsh ◽  
Joy P Misra ◽  
Jatinder Kumar

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.


Author(s):  
D. S. Sai Ravi Kiran ◽  
Sanapala Sri Ram ◽  
Tangeti Bhaskararao ◽  
Boddu Eswar Venkat Sai ◽  
Kari Suraj Kumar ◽  
...  

With numerous responses established on Taguchi L9, orthogonal array coupled with current work proposes a novel methodology for optimizing machining parameters on turning of AA 6063 T6 aluminum alloy. Experimental assessments are accomplished on AA 6063 T6 aluminum alloy. Turning trails are carried out under dry cutting conditions using an uncoated carbide insert. Cutting parameters such as cutting speed, feed rate, and depth of cut are optimized in this effort while numerous responses such as surface roughness(Ra) and material removal rate are taken into consideration (MRR). From the grey analysis, a grey relational grade(GRG) is calculated. The optimal amounts of parameters have been identified based on the values of grey relational grade, and then ANOVA is used to determine the significant influence of parameters. To authenticate the test result, a confirmation test is executed. The result of the experiments shows that by using this method. the turning process responses can be significantly improved.


2006 ◽  
Vol 505-507 ◽  
pp. 835-840 ◽  
Author(s):  
Shen Jenn Hwang ◽  
Yunn Lin Hwang ◽  
B.Y. Lee

This paper presents a new approach for the optimization of the high speed machining (HSM) process with multiple performance characteristics based on the orthogonal array with the grey relational analysis has been studied. Optimal machining parameters can then be determined by the grey relational grade as the performance index. In this study, the machining parameters such as cutting speed, feed rate and axial depth of cut are optimized under the multiple performance characteristics including, tool life, surface roughness, and material removal rate(MMR). As shown experimental results, machining performance in the HSM process can be improved effectively through this approach.


Author(s):  
Nan Zhang ◽  
Yaoyao Shi ◽  
Chen Yang ◽  
Zhen Chen ◽  
Jiang Liu

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.


2014 ◽  
Vol 1016 ◽  
pp. 172-176 ◽  
Author(s):  
Sharad Kumar Pradhan ◽  
Surendra Kumar Saini

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.


2021 ◽  
Vol 58 (2) ◽  
pp. 640-663
Author(s):  
Arti Saxena ◽  
YM Dubey ◽  
Manish Kumar ◽  
Abneesh Saxena

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.


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