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European Journal of Applied Sciences – Vol. 12, No. 4

Publication Date: August 25, 2024

DOI:10.14738/aivp.124.17391.

Le, T. P. T., Nguyen, T. Q. D., & Vu, T. T. (2024). Best Input Factors in EDM 90CrSi Using Graphite Electrodes by TOPSIS Method.

European Journal of Applied Sciences, Vol - 12(4). 285-292.

Services for Science and Education – United Kingdom

Best Input Factors in EDM 90CrSi Using Graphite Electrodes by

TOPSIS Method

Le Thi Phuong Thao

Thai Nguyen University of Technology, Thai Nguyen, Vietnam

Nguyen Thi Quoc Dung

Thai Nguyen University of Technology, Thai Nguyen, Vietnam

Vu Trung Tuyen

National Research Institute of Mechanical Engineering, Hanoi, Vietnam

ABSTRACT

This research presents a study that found the ideal process variables for Electrical

Discharge Machining (EDM) of 90CrSi using graphite electrodes. This work used a

multi-criteria decision making (MCDM) approach for the first time to produce

cylindrical-shaped parts utilizing the EDM technique and various kinds of graphite

as the electrode material. The MCDM problem was solved using the Technique for

Order of Preference by Similarity to Ideal Solution (TOPSIS) approach, and the

weights of the criteria were estimated using the Entropy method. Furthermore,

the two investigational criteria used were electrode wear rate (EWR) and material

removal rate (MRR). Furthermore, five process factors were examined: servo

voltage (SV), servo current (IP), pulse on time (Ton), pulse off time (Toff), and

graphite type (TOG). In addition, the experiment was designed and the outcomes

were assessed using the Taguchi method in Minitab R19 software. Furthermore,

for this experiment, the design L18 (6^1 + 3^4) was used. The MCDM issue has

been resolved, and the ideal process parameters were recommended.

Keywords: EDM, MCDM, TOPSIS method, Entropy method, Electrode Wear Rate,

Material Removal Rate, 90CrSi.

INTRODUCTION

Among cutting and machining techniques, EDM is the most widely used non-conventional

machining technique. It works particularly well for cutting cavity-shaped items, such plastic

molds and forging molds, among other things. A multitude of metrics, including SR, EWR,

MRR, and others, are used to assess EDM as well as other machining processes. Achieving

goals for every criterion is challenging, if not impossible, particularly when they contradict

with one another. In this situation, selecting a course of action to concurrently harmonize the

criteria must be taken into account. MCDM is the name given to this issue.

Until this point, MCDM for the EDM process has been the subject of numerous studies. The

authors report the findings of an MCDM investigation for powder-mixed electrical discharge

molding (PMEDM) of 90CrSi tool steel in [1]. The powder concentration, host voltage, pulse

duration, pulse off time, and pulse current were the input process parameters for the

investigation. In addition, three MCDM techniques were employed to tackle the issue:

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Services for Science and Education – United Kingdom 286

European Journal of Applied Sciences (EJAS) Vol. 12, Issue 4, August-2024

MARCOS (Measurement of Alternatives and Ranking according to Compromise Solution),

TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), and MAIRCA

(Multi-Attributive Ideal-Real Comparative Analysis). The weight computation for the criteria

was done using the MEREC (approach based on the Removal Effects of Criteria) approach.

Based on the results, the best option for the multi-criteria problem involving PMEDM

cylindrically shaped pieces was proposed. The authors have been given with the findings of an

MCDM analysis in [2] to establish the optimal input parameters in wire-cut EDM 90CrSi tool

steel. In this paper, the TOPSIS technique was used. The workpiece cutting radius, wire feed,

feed speed, servo voltage, cutting voltage, and pulse on and off durations were the other six

input parameters that were looked at. When machining AISI 304 stainless steel using the EDM

process, the TOPSIS technique was applied in [3] to reach minimum levels of several

performance metrics, such as average white layer thickness and SR with the maximum level of

compressive residual stress. In [4], the MCDM problem was also solved using the TOPSIS

method with the goal of obtaining a low EWR and an MRS. The MABAC (Multi-Attributive

Border Approximation Area Comparison) method has been applied to PMEDM 90CrSi tool

steel in order to identify the ideal input process variables [5]. The simultaneous achievement

of the lowest surface roughness (RS), maximum material removal speed (MRS), and maximum

electrode wear rate (EWR) is the aim of this study. Other works on MCDM that have been

done to identify the optimal input parameters for wire-cut EDM include the Measurement of

Alternatives and Ranking according to Compromise Solution (MARCOS) method [6], TOPSIS

method [7], Multi-Objective Optimization process on the basis of Ratio Analysis (MOORA

method), and TOPSIS [8]. Furthermore, utilizing the Adaptive Network based Fuzzy Inference

System approach, the white layer thickness prediction on machining treated silicon steel has

been implemented in [9]. Four different MCDM methods, including MAIRCA, MARCOS, TOPSIS,

and EAMR (Area-based Method of Ranking), were applied in [10] in order to select an

alternative that simultaneously ensures two criteria, including minimum RS and maximum

MRS. In [11], various multi-objective optimization issues are solved by using the Genetic

Algorithm (GA) and TOPSIS to determine the ideal process parameters that will yield better

MMR, Micro Hardness, low SR, EWR, and real depth.

According to the aforementioned studies, MCDM techniques have been employed in a

considerable number of studies to determine the optimal input parameters for EDM to date.

However, up until now, there hasn't been a mechanism for selecting the best input parameters

for EDM with electrodes made of various types of graphite using a MCDM approach. The

findings of an MCDM analysis using electrodes composed of several types of graphite to

choose the best input process factors in EDM 90CrSi are presented in this study. Furthermore,

this study's electrodes are designed with holes to facilitate the machining of cylindrical

workpieces. This represents the second distinction from earlier research, where electrodes

were frequently shaped like cylinders as a result of the EDM method used to produce concave

and cavities. The MCDM methodology of the study used the TOPSIS approach, and the weights

of the criteria were determined using the Entropy method. The TOPSIS method was selected

as it have been used in many previous studies [1, 12-14] to determine the optimal input

parameters for the EDM process. The optimal dressing input factors have been suggested by

applying the two criteria (EWR and MRR) from the solution of the MCDM issue.