Prediction Framework for Data-driven Design
Project status: Complete
Thrust area: New Design Paradigms and Processes
Research team: Kyoung-Yun Kim
Previous design data provide numerous means to reducing human effort and costs. For example, predicting weldability based on previous welding data can support critical assembly design decisions (e.g., material selection). Such a data-driven design application has advantages including reduced costs in physical testing for verification, improved design, and engineering efficiency. These prediction models can be used to predict critical factors during the design process that might influence the success or failure of the product.