RESUMO
Wire-electrical discharge machining (W-EDM) is a precise and efficient non-traditional technology employed to cut intricate shapes in conductive biomaterials. These biomaterials are challenging to machine using traditional methods. This present study delves into the impact of various process parameters, namely discharge duration (Ddur), spark gap time (Stime), discharge voltage (Dvolt), and wire advance rate rate (Wadv). This research evaluates the impact of several factors on response variables, namely the machining rate (MR) and surface irregularity (SR), during the machining process of the AM60B magnesium alloy. The confirmation of the material used in the machining process is achieved via the utilisation of a scanning electron microscopy (SEM) image in conjunction with an energy dispersive spectroscopic (EDS) image. The experiment is designed as L9 orthogonal array by using Taguchi's approach, taking into account 4 factors with 3 levels. The objective of this experiment is to ascertain the most favourable values for machining parameters while working with AM60B magnesium alloy using brass wire. Through analysis of variance (ANOVA), the study confirms that wire advance rate (43.10%) is the most influencing parameter for machining rate and surface irregularity followed by spark gap time (33.91%) and discharge duration (11.48%). Additionally, The TOPSIS-CRITIC and the desirability approach were used in order to determine the optimum parameter combinations that provide the most favourable combined output. Confirmatory testing is used to evaluate the efficiency of the stated ideal conditions. The maximum improvement in Desirability approach is obtained at 4.56% and 4.193% for MR and SR respectively. The maximum improvement in TOPSIS approach is obtained at 1.77% and 2.78% for MR and SR respectively.
RESUMO
The traditional way to machine hybrid composites is hard because they tend to break, have a high retraction, have a high service temperature, and have an uneven surface irregularity. For high-strength fiber/metal composite constructions, alternative machining methods have drawn interest as a solution to these problems. Current research focuses on enhancing the Abrasive Water Jet Machining process by optimizing its variables using a composite material of epoxy reinforced with silicon carbide, stainless steel wire mesh, and Kevlar. The variables assessed are the Nozzle-to-substrate gap (S), the Abrasive discharge molding and different percentages of silicon carbide (SiC) filler (0%, 3%, and 6% by weight), three different types of hybrid laminates (H1, H2, and H3) were produced. The response surface method (RSM) was utilized in this learning, specifically on a central composite design, to calculate and optimize machining variables based on the Kerf convergence ratio (Kt) and Surface irregularity (Ra) as responses. According to the results, the traverse feed velocity, Abrasive discharge proportion, and Nozzle-to-substrate gap are the critical factors in determining Surface irregularity and Kerf convergence width (H1 laminate) for a fiber/metal laminate with 0%, 3% and 6% weight fraction. In the case of a 3% weight fraction H2 laminate, the traverse feed velocity was identified as the primary factor affecting the Kerf convergence ratio. In contrast, traverse feed velocity and Nozzle-to-substrate gap had the most significant influence on Surface irregularity. The findings also indicated that S, followed by Abrasive discharge proportion and traverse feed velocity, are the variables that have the most significant influence when cutting 6 wt% SiC filler particle fiber/metal laminate (H3 laminate). For Surface irregularity, the combination of traverse feed velocity and Nozzle-to-substrate gap had the most significant impact. To validate the optimization results, confirmatory tests was conducted, and the findings were very similar to the experimental values, indicating the accuracy and effectiveness of the optimization process. To better understand the manufacturing processes, a scanning electron microscope was used to examine the morphological features of the machined surfaces, such as delamination, fibre breakage, and fibre pull-out.
