1. Introduction
Electrical discharge machining (EDM) mainly produces high-temperature melting and vaporization of materials through discharge between electrodes, so the machinability of materials mostly depends on the thermal properties of materials, such as melting point, specific heat, thermal conductivity, etc.; however the mechanical properties of materials have little effect. It uses electric energy to convert into heat energy, which generates spark discharge in a certain small gap. The instant high temperature (6000 °C~12,000 °C) causes partial melting and evaporation on the surface of the workpiece, and then the flow of the working fluid and explosion of the pressure breaks away, and then achieves a processing method of material removal [
1]. The principle of electrical discharge machining is to use resistors and capacitors to form a charging and discharging circuit, and to place conductive tool electrodes and workpieces in an insulating machining fluid. When electrical discharge machining is in progress, apply a voltage of tens to hundreds of volts between the two poles, and use the servo control system to control the tiny gap between the two poles, so that the tool electrode slowly approaches the workpiece. When the gap between the two poles reaches the maximum at a small distance from µm to tens of µm, the free ions in the machining fluid will gather due to the action of the electric field, and they will be arranged into an ion-intensive current path, which promotes the insulation breakdown of the machining fluid between the two poles, forming a plasma channel; this is called the discharge phenomenon.
The above-mentioned discharge phenomenon occurs on a small local area. When it occurs, the high temperature generated causes the surrounding machining fluid to vaporize and expand due to the high temperature, and generate a great explosion pressure, which will wash away the molten material and achieve material removal. As the molten material that is washed away is cooled rapidly due to the low temperature of the surrounding processing fluid, forming processing chips are carried away by the flowing processing fluid. Other molten metals that have not been washed away are also cooled by the insulating liquid. It re-solidifies and remains on the surface of the workpiece to form a recast layer and discharge marks. At this point, the discharge column disappears, the pressure and temperature drop, and the original insulation state between the two poles is restored, and the first discharge process is completed, and the next pulse discharge is waited. Such a repeated discharge process can reach several times per second, ranging from hundreds up to hundreds of thousands of times, and continues to repeat until the required processing depth is completed.
EDM is suitable for the processing of super-hard conductive materials. Since most ceramic materials are electrical insulators, they have rarely been processed by EDM in the past. Ceramics come in three different types: conductive, semi-conductive, and non-conductive. In recent years, with the increasing application scope of non-conductive engineering ceramic materials, the processing performance of its surface is also highly requested. However, most of these materials are typical difficult-to-process materials, and it is generally difficult to meet the processing performance requirements using traditional contact processes. In recent years, both EDM and electrochemical discharge machining (ECDM) [
2,
3,
4] have been studied to process non-conductive ceramic materials. However, the machining accuracy of ECDM still needs to be improved to meet the requirements of precision machining. In contrast, EDM still has advantages in machining accuracy and material removal rate. Since EDM is a non-contact thermo-physical process, it is necessary to re-understand the EDM process and explore its adaptability to non-conductive materials that has become another research hotspot in the field of EDM [
5,
6,
7,
8,
9].
Apart from that, Mohri et al. [
10] suggested the “Assisting Electrode Method” in the literature. In the Assisting Electrode technique, a conductive layer is applied to the surface of non-conductive ceramics. Electric sparks generate high temperatures, which cause dielectric oil hydrocarbon molecules and workpiece material molecules to break, allowing carbon to attach to particular parts of the ceramic. As carbon compounds are conductive, new discharges allow for the simultaneous machining of the deposited conductive layer and the workpiece material that was previously beneath the conductive layer. In the literature about EDM processing of non-conductive Al
2O
3 ceramic materials, Ferraris et al. [
11] investigated the micro-EDM behavior of non-conductive ceramics made of zirconium dioxide and aluminum oxide, with a secondary conductive phase added within the insulating ceramic matrix. Due to the limitation associated with electrical discharge grinding and EDM, Liu et al. [
12] devised electrical discharge milling to machine a bigger surface on a nonconductive aluminum oxide ceramic employing a thin copper sheet as an auxiliary layer. The electrical discharge machining mechanism of insulating noble sapphire crystals and three grades of high purity Al
2O
3 was also achieved by Fukuzawa et al. [
13] using the helping electrode approach. Sung et al. [
14] investigated the surface roughness and surface topography of GNP/Al
2O
3 ceramic composites using a continuous micro EDM milling method at various discharge energies. Muttamara et al. [
15] compared the effect of the generation of conductive layers on alumina corresponding to EDM properties using copper, graphite and copper-impregnated graphite electrodes. It was found that the MRR value increased by 60% for the bipolar EDM-3. The surface roughness was improved to 25 μm at the anode of EDM-C3. Ji et al. [
16] efficiently use high energy capacitors for EDM of insulating ceramics. The results show that high voltage, large capacitors, and high discharge energy can effectively process the insulating ceramic into EDM, and the single discharge crater volume of the insulating ceramic can reach 17.63 mm
3. Liu et al. [
17] present a new process for processing insulating ceramics using electric discharge (ED) milling cutters. The ED milling machine uses a water-based emulsion as the processing fluid, using a thin copper sheet as an auxiliary electrode, which is fed to the tool electrode along the surface of the workpiece. By using the flow rate of the machining fluid, the ED milling MRR is increased and the SR change is small. Liu et al. [
18] uses a thin copper sheet fed to the tool electrode along the workpiece surface as an auxiliary electrode using an aqueous emulsion as the processing fluid. It can effectively treat large surface areas on insulating ceramics. The study results show that insulating Al
2O
3 ceramics are removed by a single pulse discharge under the influence of dissolution, evaporation, and delamination. The relevant ceramic EDM literature review is detailed in the review paper [
19].
Dr. Genichi Taguchi developed the Taguchi Approach, which was a standardized Design of Experiment (DOE) method for identifying the optimum combination of variables under specified experimental circumstances [
20]. The Taguchi approach [
21] consists of three basic steps: orthogonal array selection, S/N ratio calculation, and analysis of variance (ANOVA). With a limited number of trials, an orthogonal array was designed to explore the whole parameter space [
22,
23]. Signal-to-noise ratio (S/N) identifies an optimal control factor setting that will make a process or product robust or tolerant of changes in noise factor. ANOVA was used to study the influence of process parameters on the machining process [
24]. This method was best suited for single-performance optimization [
25,
26]. However, most industrial processes involve multi-response issues. As a result, a single-performance optimization issue may be converted into a multi-performance optimization problem using the Taguchi technique and the idea of Multi-Criteria Decision Making (MCDM). To choose the best processing conditions, the MCDM approach can be utilized.
The TOPSIS method was first proposed by Hwang and Yoon [
27] that order preference method by similarity to ideal solution. The TOPSIS technique was an MCDM method for finding the best answer from a set of options when dealing with multiple criterion issues. The optimum solution has the smallest distance from the positive ideal solution and was the furthest away from the negative solution, according to the main principle of this approach. Therefore, TOPSIS based Taguchi optimization provides a useful approach to convert multi-performance simulation–optimization problem into the single-performance problem. In manufacturing, assessing multi-performance at the same time was an important issue. Balasubramaniyan, S. [
28] used a combination of Taguchi and TOPSIS techniques to find the best process parameters for turning EN25 steel using coated carbide tools. Nahak, P. [
29] applied TOPSIS and Taguchi method in turning austenitic stainless steel. TOPSIS and Taguchi method was to find the optimum machining parameters so as to minimize the surface roughness and tool cutting forces and maximize the material removal rate for the selected tool and work materials in the chosen domain of the experiment. Muqeem, M. [
30] used the Taguchi-based entropy-weighted TOPSIS method to optimize the performance and emission parameters of diesel engines.
EDM process modeling and optimization in the EDM process is essential for multiple performance characteristic issues. Kasdekar, D. K. [
31] proposed an entropy based TOPSIS, Simple Additive Weighting (SAW) methods to solve the multi-performance parameter optimization problem in EDM. Tripathy, S [
32] using Taguchi method in combination with TOPSIS and grey relational analysis evaluated the effectiveness of optimizing multiple performance characteristics for powder mixed EDM of H-11 die steel using copper electrode. Vaddi, V. R. [
33] focused on applying the Taguchi method and TOPSIS to optimize machining parameters in EDM of titanium alloys (Ti-6Al-4V), considering multiple performance issues. All of the findings showed that TOPSIS with Taguchi method was capable of addressing numerous objective issues involving EDM. A multi-performance problem was converted into a single equivalent objective problem using this technique. With the framework of a hierarchy of criteria, stakeholders, and results, and by drawing considerations for generating weights or priorities, this Analytic Hierarchy Process (AHP) approach [
34] aids in the solution of complicated issues. It also synthesizes different factors into outcomes that intuitively meet our expectations, combining the powers of sentiments and rationality focused on various topics. An AHP model’s structure is that of an inverted tree. The objective of the decision-making problem is represented by a single purpose at the top of the tree. At this moment, the decision weight is 100 percent. A leaf point appears just below the objective, showing the qualitative and quantitative requirements. The goal weight should be distributed among the rating points according to the rating. In related literature, Nadda R. [
35] used the hybrid AHP TOPSIS method to improve the surface roughness of cobalt-bonded tungsten carbide composites in EDM, maximize material removal rates, and minimize tool wear rates using optimal control parameter settings. We know that few studies have been reported on the application of the Taguchi method and TOPSIS method of EDM of non-conductive materials with multiple performance characteristics according to literature review.
As a result, the goal of this research is to determine the best process parameters for electrical discharge machining of non-conductive materials. Another important aspect of this study is that the TOPSIS method coupled with AHP method (which calculates relative weight of the performance variables) has been used to solve multi-performance optimization problem of EDM of non-conductive materials. The L18 orthogonal array of Taguchi method is used to conduct experiments. TOPSIS method is applied to determine the optimum conditions of process parameters to yield maximum MRR and minimum EWR simultaneously. The study results presented are significantly useful for researchers and professionals related to EDM of non-conductive materials with multiple performance characteristics.