Weldability Prediction of AHSS Stackups Using Artificial Neural Network Models

Paper #:
  • 2012-01-0529

Published:
  • 2012-04-16
Citation:
Sohmshetty, R., Ramachandra, R., Coon, T., Kim, K. et al., "Weldability Prediction of AHSS Stackups Using Artificial Neural Network Models," SAE Technical Paper 2012-01-0529, 2012, https://doi.org/10.4271/2012-01-0529.
Pages:
14
Abstract:
Typical automotive body structures use resistance spot welding for most joining purposes. New materials, such as Advanced High Strength Steels (AHSS) are increasingly used in the construction of automotive body structures to meet increasingly higher structural performance requirements while maintaining or reducing weight of the vehicle. One of the challenges for implementation of new AHSS materials is weldability assessment. Weld engineers and vehicle program teams spend significant efforts and resources in testing weldability of new sheet metal stack-ups. In this paper, we present a methodology to determine the weldability of sheet metal stack-ups using an Artificial Neural Network-based tool that learns from historical data. The paper concludes by reviewing weldability results predicted by using this tool and comparing with actual test results.
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