The value of competently-executed system models will continue to increase as digital transformation efforts gain momentum in aerospace, defense, automotive, and other industries. However, for organizations to reap the full value of their modeling investment, modelers must create internally consistent models that not only support concept exploration and analysis but also conform to modeling guides, ontologies, and constraints levied by middleware and the need for data interchange.

This presentation will emphasize pragmatic usage of model customization to support decision-making and model queries; it will also demonstrate methods to generate meaningful model metrics and develop validation suites that ensure model quality.