Fast Prediction for Resistance Spot Welding Deformation Using Inherent Strain Method and Nugget Model

Area of Science:

• Manufacturing Engineering
• Materials Science
• Computational Mechanics

Background:

• Car bodies utilize thousands of resistance spot welds, which can cause significant deformation during manufacturing.
• Current methods for predicting welding-induced deformation are often computationally intensive and time-consuming.
• The inherent strain method, successful for arc welding, has not been applied to resistance spot welding.

Purpose of the Study:

• To develop and validate an efficient method for predicting resistance spot welding deformation in automotive structures.
• To adapt the inherent strain method for the specific challenges of resistance spot welding.
• To provide automotive industries with a faster and simpler deformation prediction tool.

Main Methods:

• Development of a specialized nugget model for resistance spot welds.
• Extension of the inherent strain method to model resistance spot welding processes.
• Validation of the extended inherent strain method against experimental measurements.

Main Results:

• The inherent strain method was successfully extended to predict resistance spot welding deformation.
• Deformation prediction for a vehicle part with 23 welds was achieved in approximately 90 minutes.
• The predicted deformations showed good accuracy when compared to measured data.

Conclusions:

• The inherent strain method offers an efficient and accurate approach for predicting resistance spot welding deformation.
• This method significantly reduces computation time compared to traditional coupled analyses.
• The developed technique can aid automotive industries in optimizing manufacturing processes and managing deformation.