scholarly journals Grey Relational Analysis Optimization of Input Parameters for Electrochemical Discharge Drilling of Silicon Carbide by Gunmetal Tool Electrode

2020 ◽  
Vol 44 (4) ◽  
pp. 239-249
Author(s):  
Pravin Pawar ◽  
Amaresh Kumar ◽  
Raj Ballav
Keyword(s):  
Silicon Carbide ◽  
Grey Relational Analysis ◽  
Electrolyte Concentration ◽  
Research Work ◽  
Machining Process ◽  
Advanced Technology ◽  
Tool Electrode ◽  
Relational Analysis ◽  
Electrochemical Discharge ◽  
Grey Relational

The electrochemical discharge machining process (ECDM) is a hybrid advanced technology integrated with electrochemical and electro-discharge processes has used for the manufacturing of non-conducting along with conducting materials. The silicon carbide is non-conducting material which has widely used in various fields such as automobile, aviation, medical, nuclear reactor, and missile. The machining of silicon carbide is a challenging task by using non-conventional along with conventional machining processes due to its physical properties. The current research work shows the machining of Silicon carbide material by using fabricated ECDM machine setup with gunmetal tool material. The Taguchi L27 orthogonal array technique is applied for experimental work. The grey relational analysis optimization is applied for the investigation of optimum input factors for better output responses. The input process factors like electrolyte concentration, applied voltage, and rotation of tool and outcome results such as machined depth and the diameter of hole were checked after drilling of silicon carbide material. The experimental results indicate the electrolyte concentration is the leading factor for diameter of hole and depth of machined hole subsequent to voltage and tool rotation.

scholarly journals Grey Relational Analysis of EDM of Ti6Al4V using TiC/Cu Composite Tool Electrode Made with Nano and Micron Sized Particles

2019 ◽  
Vol 9 (1) ◽  
pp. 6154-6162
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Optimum Combination ◽  
Ti6al4v Alloy ◽  
Machining Process ◽  
Dominant Factor ◽  
Tool Electrode ◽  
Peak Current ◽  
Relational Analysis ◽  
Grey Relational

This paper covers the use of Taguchi based grey relational analysis in EDM process. The analysis is used to determine an optimum combination of process parameters, which involves individual and simultaneous improvement of surface roughness (SR) and the micro hardness (MH) of Ti6Al4V alloy in electric discharge machining (EDM). The tool used in the machining process is TiC/Cu powder metallurgy (P/M) electrode. Taguchi’s L18 mixed orthogonal array is used to plan experimentations which includes the machine tool and electrode parameters as the study parameters. The analysis of variance (ANOVA) for grey relational grade showed that particle size EDM electrode was the most dominant factor (64.13%) followed by peak current (7.41%) in influencing surface quality of EDMed Ti6Al4V alloy. Whereas, peak current is the most influential parameter while evaluating the individual responses of SR and MH. Finally, the optimum combination of process parameters was validated by confirmation experiments that considerably improved the multiple quality characteristics simultaneously.

Analysis and Optimization of Wire EDM Process of Titanium by Using GRA Methodology

2019 ◽  
Vol 969 ◽  
pp. 678-684 ◽  
Author(s):  
Sarat Kumar Sahoo ◽  
A. Bara ◽  
A.K. Sahu ◽  
S.S. Mahapatra ◽  
D.S. Kiran ◽  
...  
Keyword(s):  
Grey Relational Analysis ◽  
Orthogonal Array ◽  
Electrical Discharge Machining ◽  
Input Parameter ◽  
Optimization Technique ◽  
Research Work ◽  
Cutting Speed ◽  
Machining Process ◽  
Relational Analysis ◽  
Grey Relational

In this research work, an efficient optimization technique, grey relational analysis (GRA) has been used to for optimization of wire electrical discharge machining process of Titanium (grade 2) by considering multiple output parameters. This technique combines Taguchi’s orthogonal array with grey relational analysis for the design of the experiment. The central focus of this research is to achieve improved Kerf width, surface roughness and cutting speed. GRA method is implemented to decide the best input parameter that optimizes the output parameters. This study has been conducted by applying Taguchi’s L9 orthogonal array. Each experiment has been conducted in altered conditions of input variables. For the optimization of multiple criteria, GRA is suggested as a suitable technique for the optimization of complex interrelationships between multi-performance characteristics. By analysis of variance (ANOVA) it is found that the percentage of contribution of peak current on overall performance is maximum i.e.73.1%.

Optimization of the Wire Electrical Discharge Machining Process Using Grey Relational Analysis and Taguchi Method

2015 ◽  
Vol 651-653 ◽  
pp. 738-743
Author(s):  
Oana Dodun ◽  
Vasile Merticaru ◽  
Laurenţiu Slatineanu ◽  
Margareta Coteaţă
Keyword(s):  
Taguchi Method ◽  
Grey Relational Analysis ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Machining Process ◽  
Tool Electrode ◽  
Wire Electrical Discharge Machining ◽  
Relational Analysis ◽  
The Wire ◽  
Grey Relational

The wire electrical discharge machining is a machining method able to allow detaching parts from plates type workpieces as a consequence of electrical discharges developed between workpiece and wire tool electrode found in a motion along its axis; there is also a work motion along the contour to be obtained. There are many factors able to exert influence on the sizes of parameters of technological interest. On the other hand, there are various methods that can be used in order to establish the optimal combination of the input factors, so that obtaining of machining best results is possible. When there are many process output factors, a problem of multiobjective optimization could be formulated. The Grey relational analysis method and the Taguchi method could be applied in order to optimize the wire electrical discharge machining process, when various criteria having distinct significances are considered. An experimental research was designed and developed in order to optimize the wire electrical discharge cutting of parts made of an alloyed steel, by considering six input factors: test piece thickness, pulse on time, pulse off time, wire axial tensile, current intensity and travelling wire electrode speed. As output parameters, one took into consideration surface roughness, wire tool electrode massic wear, cutting speed along the contour to be obtained. 16 experiments were developed in accordance with the requirements specific to a Taguchi table L16. The results of experiments were processed by means of Grey relational analysis method and Taguchi method.

scholarly journals Multi-Response Optimization of Coagulation and Flocculation of Olive Mill Wastewater: Statistical Approach

2021 ◽  
Vol 11 (5) ◽  
pp. 2344
Author(s):  
Srikanth Vuppala ◽  
Riyaaz Uddien Shaik ◽  
Marco Stoller
Keyword(s):  
Grey Relational Analysis ◽  
Research Work ◽  
Olive Mill Wastewater ◽  
Relational Analysis ◽  
Coagulation And Flocculation ◽  
Coagulant Dosage ◽  
Response Optimization ◽  
Grey Relational ◽  
Flocculation Process ◽  
Olive Mill

Olive oil production is one of the important industrial sectors within the agro-food framework of the Mediterranean region, economically important to the people working in this sector, although there is also a threat to the environment due to residues. The main wastes of the olive oil extraction process are olive mill wastewater (OMW) and olive husks which also require proper treatment before dismissal. In this research work, the main goal is to introduce grey relational analysis, a technique for multi-response optimization, to the coagulation and flocculation process of OMW to select the optimum coagulant dosage. The coagulation and flocculation process was carried out by adding aluminum sulfate (Alum) to the waste stream in different dosages, starting from 100 to 2000 mg/L. In previous research work, optimization of this process on OMW was briefly discussed, but there is no literature available that reports the optimal coagulant dosage verified through the grey relational analysis method; therefore, this method was applied for selecting the best operating conditions for lowering a combination of multi-responses such as chemical oxygen demand (COD), total organic carbon (TOC), total phenols and turbidity. From the analysis, the 600 mg/L coagulant dosage appears to be top ranked, which obtained a higher grey relational grade. The implementation of statistical techniques in OMW treatment can enhance the efficiency of this process, which in turn supports the preparation of waste streams for further purification processes in a sustainable way.

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