Digital Engineering and Advanced Manufacturing

The digital transformation of manufacturing requires digitalization, including automatic and efficient data exchange. Model-based definitions (MBDs) capture digital product definitions to eliminate error-prone information exchange associated with traditional paper-based drawings and provide contextual information through additional metadata. The flow of MBDs extends throughout the product lifecycle (including the design, analysis, manufacturing, in service life, and retirement stages) and can be extended beyond the typical geometry and tolerance information within a computer-aided design. We have extended MBDs to include materials information, via dynamic linkages. Model-based feature information network (MFIN) has been created to provide a comprehensive framework that facilitates storing, updating, searching, and retrieving of relevant information across a product’s lifecycle.  

Through these model-based definitions, focusing on materials’ microstructure and defect, the manufacturing process can be transformed or refined to produce components with enhanced properties.    
 
Dr. Sangid has been part of working groups that have shaped the ideas and concepts of the digital twin definition and value.  A digital twin: (i) is a set of virtual information constructs that mimics the structure, context, and behavior of an individual / unique physical asset, (ii) is dynamically updated with data from its physical twin throughout its life cycle, and (iii) informs decisions that realize value. Digital twins use current state awareness of a physical asset to facilitate reduced uncertainty in predictions of future events.