Semantic Scholar Open Access 2023 53 sitasi

Multiphysics Simulation of the Shape Prediction and Material Removal Rate in Electrochemical Machining Process

Pankaj Kumar Amit Kumar Jain J. Srivastava R. Kumar K. Saxena +2 lainnya

Abstrak

ABSTRACT The electrochemical machining process involves electrical and chemical processes while removing materials from the workpiece. Electrochemical machining (ECM) lacks accurate models for predicting the shape and material removal rate during the ECM process. This limits the ability to optimise the process and predict the final product geometry, which is crucial for industrial applications. This research mainly focused on the modelling and simulation of material removal from the workpiece using COMSOL Multiphysics software. This research involves developing a mathematical model that describes ECM’s electrical, chemical, and mechanical interactions. The model is based on electrochemistry, fluid dynamics, and solid mechanics principles and will be solved using numerical simulation techniques. Various workpiece materials considered in this investigation include Aluminium, Nickel, Stainless Steel, and Tungsten, whereas copper is electrode material. The effects of the various parameters, such as workpiece materials, the voltage applied during machining, and electrolyte conductivity on the material removal rate are being investigated. In addition, the shape of the machined workpiece is also predicted. The results of this research provide a deeper understanding of the underlying physics of the ECM process and lead to the development of more accurate models for predicting the shape and material removal rate during ECM.

Penulis (7)

P

Pankaj Kumar

A

Amit Kumar Jain

J

J. Srivastava

R

R. Kumar

K

K. Saxena

C

C. Prakash

D

D. Buddhi

Format Sitasi

Kumar, P., Jain, A.K., Srivastava, J., Kumar, R., Saxena, K., Prakash, C. et al. (2023). Multiphysics Simulation of the Shape Prediction and Material Removal Rate in Electrochemical Machining Process. https://doi.org/10.1080/2374068X.2023.2192132

Akses Cepat

Informasi Jurnal
Tahun Terbit
2023
Bahasa
en
Total Sitasi
53×
Sumber Database
Semantic Scholar
DOI
10.1080/2374068X.2023.2192132
Akses
Open Access ✓