1. Introduction
The thermal sintering technique is employed to manufacture 316L porous stainless steel (PSS). Sintering of the metal powders is performed inside a controlled environment, at a temperature below the melting point of the base metal [
1]. PSS has low cost, easy availability, good workability, high fatigue life, fracture toughness, low density, large specific surface area, excellent energy absorbtion properties, electrical conductivity, weldability, and ductility of metallic materials [
2]. Porous metals such as titanium and titanium alloys, cobalt chrome, nitinol shape memory alloys, and stainless steel 316L are generally employed for biomedical and membrane filtration applications [
3]. Among these materials, SS316L porous metals have become a suitable candidate for bio-materials, which can increase bone fixation and are extensively used in hip and knee replacement surgery [
4]. The PSS has excellent lightweight and damping properties and superior mechanical and metallurgical properties. Porous SS316L metal membranes are employed to filtrate a gas mixture of CO and
at temperatures up to 250 °C and 8 MPa for 4 months with excellent filtration characteristics [
5]. The materials selection and different manufacturing techniques for various industrial applications of porous metal membranes, such as membrane contractor, membrane bioreactor, catalytic metal membranes, etc., are critically reviewed by Singh et al. [
6].
The presence of interconnected pores leads to ventilation and breathing characteristics in porous SS316L. The presence of such excellent characteristics of PSS are highly suitable for metal membrane and die casting [
7]. Furthermore, due to the presence of interconnected pores, the evacuation of air is easily possible. However, conventional machining process such as turning, milling, and grinding deteriorate the pores’ interconnectivity properties. Hence, the breathing capacity of the PSS diminishes. This phenomenon decreases the mechanical and metallurgical characteristics of PSS. Thus, non-conventional machining technology is recommended to preserve the properties of porous SS316L. Furthermore, to reduce the thickness of porous metal membranes and generate complex three-dimensional geometries with higher manufacturing efficiency and good surfaces, EDM machining is essential. Wang et al. [
8] have investigated the influence of porosity and pore size of ASISI 304 PSS on micro-EDM machining characteristics. The porous substrates are employed to enhance biological fixation on orthopedic implants. In the case of fixation of sensors and other devices, the drilling of PSS is essential. Hence, a high surface finish and accuracy of the machined surface are desired. These features can easily be generated by the EDM machining process [
9]. Kumar et al. [
10] have worked on multivariable optimization in EDM machining AISI 420 stainless steel with a Taguchi-grey technique. Sanjeev et al. [
11] have investigated single optimization in EDM machining of stainless steel 316L using Taguchi design. Suresh et al. [
12] have employed a response surface methodology for the micro-EDM machining of stainless steel 316L. The genetic algorithm is used for single-objective optimization to achieve higher MRR values.
As there is very little literature available on the EDM of PSS, it is essential to analyze the EDM performance in machining porous SS316L to enhance the MRR and reduce the TWR values. The EDM of porous metal requires optimal process parameters, which significantly benefits manufacturing industries in terms of improved product quality, reduced machining cost, enhanced productivity, etc. Sahoo et al. [
13] have experimented on high carbon, high chromium steel, as a workpiece and brass as wire electrode material. They have designed the experiments using Taguchi
orthogonal array, and machining process parameters are optimized by employing multi-objective optimization by ratio analysis (MOORA) method. Nguyen et al. [
14] used the Taguchi Data Envelopment Analysis based Ranking (DEAR)-based multi-criteria decision-making technique to obtain optimal EDM process parameters in machining silicon-based steel with a low-frequency vibration assisted EDM process. Bhiksha et al. [
15] have investigated the effect of graphite powder concentration in EDM machining on Ti-6Al-4V alloy. They have used Grey relational analysis for the multi-response optimization of EDM process parameters. Pratap et al. [
16] performed the EDM machining of Inconel-X 750. They employed an approach integrating Weightage principal component analysis using Taguchi theory (WPCA-Taguchi).
Nature-inspired heuristic optimization techniques have been shown to be better than deterministic methods and are extensively used. Hence, meta-heuristic optimization techniques are extensively utilized to improve the desired manufacturing process in modern industries [
17]. These techniques solve numerous complex, multimodel, and large-dimensional or discontinuous problems and deliver acceptable solutions to complicated problems. The results obtained from such techniques are found to produce solutions that are improved compared to deterministic techniques [
18]. These nature-inspired meta-heuristic techniques, such as genetic algorithm (GA), are based on Darwin’s theory of biological evolution, i.e., survival of the strongest. The artificial bee colony (ABC) is inspired by the collective behavior of social insect colonies and other animal societies. Ant colony optimization (ACO) is based on stigmergy and foraging for food sources [
19]. In meta-heuristic optimization problem computation, the target is to obtain the global optima. However, this optimum value can only be estimated by forming a fitness function curve using the regression equation of the objective function. In the case of traditional optimization techniques, the formation of the fitness function curve is not attempted. Hence, there is a need for a proper fitness curve so that the local and global optima regions can easily be determined feasibly.
There is limited research published on the application of TLBO and PSO in non-conventional machining processes, especially in the EDM processing of porous metals, and it is yet to be explored. Therefore, the present work aims to obtain the optimum machining process parameters in the EDM of porous sintered SS316L by using the TLBO and PSO algorithms to maximize the MRR and minimize the TWR values. In addition, analysis of variance analysis (ANOVA) is performed to determine the influence of different EDM process parameters and different porosity values of sintered porous SS316L on MRR and TWR values. The final optimized results using two intelligent algorithms, TLBO and PSO, were further analyzed comparatively. The present study’s findings contribute valuable information in regulating the EDM performance in machining porous SS316L.