As a successful solution applied to electrical discharge machining (EDM), powder-mixed electrical discharge machining (PMEDM) has been proposed as an upgrade of the EDM process. The optimization of the process parameters of PMEDM is essential and pressing. In this study, Taguchi methods and analysis of variance (ANOVA) were used to find the main parameters affecting surface roughness in the EDM process with SiC powder-mixed-dielectric of hardened 90CrSi steel. The PMEDM parameters selected were the powder concentration, the pulse-on-time, the pulse-off-time, the pulse current, and the server voltage. It was found that SiC powder exhibits positive effects on reducing surface roughness. The roughness obtained with the optimum powder concentration of 4 g/L was reduced by 30.02% compared to that when processed by conventional EDM. Furthermore, the pulse-off-time was found to be the most influential factor that gave an important effect on surface roughness followed by the powder concentration. The EDM condition including a powder concentration of 4 g/L, a pulse-on-time of 6 µs, a pulse-off-time of 21 µs, a pulse current of 8 A, and a server voltage of 4 V resulted in the best surface roughness.

When optimizing a mechanical device, the symmetry principle provides important guidance. Minimum gearbox mass and maximum gearbox efficiency are two single objectives that need to be achieved when designing a gearbox, and they are not compatible. In order to address the multi-objective optimization (MOO) problem with the above single targets involved in building a two-stage helical gearbox with second-stage double gear sets, this work presents a novel application of the multi-criteria decision-making (MCDM) method. This study’s objective is to identify the best primary design elements that will increase the gearbox efficiency while lowering the gearbox mass. To carry this out, three main design parameters were selected: the first stage’s gear ratio and the first and second stages’ coefficients of wheel face width (CWFW). Furthermore, a study focusing on two distinct goals was carried out: the lowest possible gearbox mass and the highest possible gearbox efficiency. Furthermore, the two stages of the MOO problem are phase 1 and phase 2, respectively. Phase 2 solves the single-objective optimization issue to minimize the difference between variable levels and the MOO problem to determine the optimal primary design factors. To solve the MOO problem, the EAMR (Evaluation by an Area-based Method of Ranking) method was also chosen. The following are important features of this study: First, a MCDM method (EAMR technique) was successfully applied to solve a MOO problem for the first time. Secondly, this work explored the power losses during idle motion to calculate the efficiency of a two-stage helical gearbox with second-stage double gear sets. This study’s findings were used to identify the optimal values for three important design variables to design a two-stage helical gearbox with second-stage double gear sets.

Electrical discharge machining represents a non-conventional machining process, specifically designed for the effective fabrication of materials that are difficult to machine and for components with complex geometries. Many studies have been carried out that combine electrical discharge machining with the ultrasonic vibration of electrodes. Nevertheless, most of these investigations have concentrated on the processing of hole or cavity components. This document presents an experimental study focused on the design of an electrode holder for ultrasonic vibration electrical discharge machining, focusing on the machining of cylindrical surfaces. This study involved a two-stage design process for the electrode holder, aimed at determining the optimal length to achieve the maximal material removal rate and to ensure surface roughness. The novel aspect of this study is that it is the first to be published on the use of ultrasonic vibration in the electrical discharge machining process for processing cylindrical surfaces. Furthermore, splitting the electrode holder design process into two stages (theoretical calculation and experimental determination) made it possible to identify an electrode holder design for ultrasonic vibration electrical discharge machining that increased the MRR by 35.5% while maintaining SR values that were similar to those produced during the electrical discharge machining without ultrasonic vibration.

Ultrasonic Vibration-Assisted Electrical Discharge Machining (UV-EDM) constitutes a promising technique for improving machining efficiency and surface quality, particularly when working with difficult-to-machine materials. This study presents a comprehensive multi-objective optimization approach for UV-EDM applied to 90CrSi steel, aiming to maximize the Material Removal Rate (MRR) while minimizing Surface Roughness (Ra). The experimental data were collected under varying process parameters, including the peak current, pulse-on time, and ultrasonic vibration amplitude. A Gaussian Process Regression (GPR) model was developed to accurately predict MRR and Ra. These predictive models were then integrated into the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) to perform Pareto-based optimization. Additionally, the Analytic Hierarchy Process (AHP) was employed to rank the Pareto-optimal solutions based on decision-makers’ preferences. The results demonstrate the effectiveness of combining GPR and NSGA-II for modeling and optimizing UV-EDM, while the use of AHP enables a rational selection of optimal machining conditions. This hybrid methodology offers valuable insights into enhancing productivity and surface integrity in precision machining applications.