Criteria for Predicting Skid Line by Simulation

2017-01-0300

03/28/2017

Features
Event
WCX™ 17: SAE World Congress Experience
Authors Abstract
Content
The risk of skid lines for Class A panels has to be assessed before releasing the die development for hard tooling. Criteria are needed to predict skid lines in the formability evaluation stage to avoid expensive changes to tooling and process for resolving skid line issue in production. In this study, criteria using three different measured parameters were developed and validated. A draw-stretch-draw (DSD) test procedure was developed to generate skid lines on lab samples for the physical evaluation. This was done using tooling with various die entry radii and different draw beads. The skid line severity of lab samples was rated by specialists in the inspection of automotive outer panel surface quality. The skid line rating was correlated with geometric measurements of the lab samples after the DSD test. The sensitivity of the appearance of skid lines to tooling and process parameter variations was identified. Finite element simulation was conducted to correlate with test measurements, to understand the reason of skid lines and discover the critical conditions to have visible skid lines. By correlating variables obtained in post processing to skid line rating, criteria based on both thickness and strain were developed to define the limit for a visible skid line. This was then implemented in a stamping simulation of a hood outer. The areas on the hood where skid lines were observed were predicted with the simulation using the developed criteria. More simulation implementation, industrial evaluation and validation may help to improve the accuracy of the criteria.
Meta TagsDetails
DOI
https://doi.org/10.4271/2017-01-0300
Pages
11
Citation
Yao, H., Sadagopan, S., Kuo, M., Huang, L. et al., "Criteria for Predicting Skid Line by Simulation," SAE Technical Paper 2017-01-0300, 2017, https://doi.org/10.4271/2017-01-0300.
Additional Details
Publisher
Published
Mar 28, 2017
Product Code
2017-01-0300
Content Type
Technical Paper
Language
English