A Finite Element Analysis of Cold Deep Drawing of Al Alloy Considering Friction Condition and Corner Design of Plunger

• Published in: Lubricants Vol. 11; no. 9; p. 388
• Main Authors: Bahanan, Warda, Fatimah, Siti, Go, Jae Hoon, Oh, Jeong Moo, Kim, Min Jun, Kim, Myung Jae, Kang, Jee-Hyun, Kim, Dong-Ju, Widiantara, I Putu, Ko, Young Gun
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.09.2023
• Subjects: Al alloy; Alloys; Aluminum; Aluminum base alloys; Analysis; Anisotropy; Bending; Coefficient of friction; Cold; cold deep drawing; Cold drawing; Cost analysis; Deep drawing; Deformation; Digital imaging; Ductility; Efficiency; Empirical analysis; Failure; Finite element analysis; Finite element method; Friction; friction coefficient; Manufacturers; Manufacturing; Mechanical properties; Metal products industry; plunger radius; Simulation; Simulation methods; Strain analysis; Strain distribution; Strain rate; Success; Temperature
• ISSN: 2075-4442; 2075-4442
• DOI: 10.3390/lubricants11090388

This study presents an innovative methodology that integrates experimental investigations with finite element simulations to ascertain the validity and reliability of Al 3104 sheet metals during cold deep drawing. Focusing on the nose plunger radius and coefficient of friction at a fixed speed and temperature (25 °C), five different scenarios are utilized to simulate the optimum parameters. Through a detailed strain history analysis from simulations, the initiation of bending in the corner is precisely identified, with a validation achieved through a strain analysis obtained via digital image correlation. The study delves into the influence of strain and strain rate on the microstructures and mechanical properties near the corner region. It highlights the superior efficacy of strain-based criteria in characterizing deformation behavior. Notably, the strain distributions during the onset of bending and severe bending align remarkably well with the established simulation data. In brief, this work introduces an integrated approach that harmoniously combines computational simulations with empirical observations, resulting in significant ramifications for precisely comprehending and forecasting the strain distribution in metal forming operations.