Integration and visualization framework for data-driven resistance spot welded assembly design

Recently, data-driven design and manufacturing provide industries potential competitive edge. With this emerging paradigm, designers can make efficient design decisions considering various manufacturing process data. Resistance Spot Welding (RSW) process is well utilized in various manufacturing industries including the automotive industry. However, the utilization of the RSW process data is still limited due to the disconnected welded assembly design models and associated process data challenges. This article presents a framework to integrate and visualize the welded assembly design and weldability knowledge extracted from RSW process datasets. In this article, a design database stores the geometric assembly design information and the STM (SpatioTemporal Mereotopology) ontology is connected to the design database. For this study, a real industry RSW test datasets are utilized to extract weldability decision rules with data mining algorithms. To build a shareable RSW weldability knowledge, an RSW ontology is utilized. Afterward, welded assembly design and weldability knowledge sets are extracted from the two ontology-based models and integrated with a X3DOM data to visualize the assembly design and weldability knowledge. Finally, multiple welded assembly models are generated and tested with the developed visualization framework.