Trias Andromeda

TL;DR: In this article, the authors compared a Dimensional Analysis (DA) model, an Artificial Neural Network (ANN) model and an experimental result for a low gap current of an Electrical Discharge Machining (EDM) process.

TL;DR: In this paper, a behavioral model is used to predict material removal rate (MRR) in electrical discharge machining (EDM) using Artificial Neural Network (ANN) using experimental data were gathered from die sinking EDM process for copper-electrode and steel-workpiece.

TL;DR: In this article, an Artificial Neural Network (ANN) architecture was used to model the electrical discharge machining (EDM) process using an input-output pattern of raw data collected from an experimental of EDM process, whereas several research objectives have been outlined such as experimenting machining material for selected gap current.

TL;DR: In this article, a new micro-electrical discharge machining controller model using Particle Swarm Optimization algorithm for efficient search and optimization of Proportional-Integral controller parameters in order to achieve a better positioning system especially in biomedical application.

TL;DR: Simulation results verify the capabilities and effectiveness of the DE algorithm to search the best configuration of PID gain to maintain the electrode position and identify suitable gain parameters for servo actuator system.