Friction Coefficient Evaluation on Aluminum Alloy Sheet Metal Using Digital Image Correlation

2018-01-1223

04/03/2018

Features
Event
WCX World Congress Experience
Authors Abstract
Content
The coefficient of friction between surfaces is an important criterion for predicting metal behavior during sheet metal stamping processes. This research introduces an innovative technique to find the coefficient of friction on a lubricated aluminum sheet metal surface by simulating the industrial manufacturing stamping process while using 3D digital image correlation (3D-DIC) to track the deformation. During testing, a 5000 series aluminum specimen is placed inside a Stretch-Bend-Draw Simulator (SBDS), which operates with a tensile machine to create a stretch and bend effect. The friction coefficient at the contact point between an alloy sheet metal and a punch tool is calculated using an empirical equation previously developed. In order to solve for the unknown friction coefficient, the load force and the drawback force are both required. The tensile machine software only provides the load force applied on the specimen by the load cell. Thus, the drawback force requires an indirect method of measurement. In this presentation, a method is proposed that uses DIC to measure tensile strain on a specimen’s surface to acquire the drawback force. This requires first collecting preliminary data to determine a tensile strain and drawback force relationship. Once this force-strain relation is established, the tests to determine the friction coefficient can be performed and the friction coefficient is determined from the results of the final test data. The concept, set-up, procedure, and results of this research will be presented in detail.
Meta TagsDetails
DOI
https://doi.org/10.4271/2018-01-1223
Pages
8
Citation
Duan, E., Li, J., Schaeffler, D., Wang, H. et al., "Friction Coefficient Evaluation on Aluminum Alloy Sheet Metal Using Digital Image Correlation," SAE Technical Paper 2018-01-1223, 2018, https://doi.org/10.4271/2018-01-1223.
Additional Details
Publisher
Published
Apr 3, 2018
Product Code
2018-01-1223
Content Type
Technical Paper
Language
English