Abstract
A data-centric approach is proposed to facilitate the design and analysis of challenging complex systems and address the problems of currently existing model-based systems engineering (MBSE) methodologies. More specifically, based on three core steps of current MBSE methodologies, a high-level data meta-model, depicting the semantic relationships of high-level data concepts, is first presented to guide the data modeling for systems engineering (SE). Next, with respect to the six high-level data concepts, the data elements are collected as the modeling primitives to construct static and/or executable models, which can also act as a common and consistent data dictionary for SE. Then, the mapping associations amongst core data elements are established to associate the model elements in different steps and achieve the requirement traceability matrix. Finally, the feasibility of the proposed approach is demonstrated with an illustrative example.
Developing A Supply Chain Of Apple Processed Product Traceability Information System Based On Smart Packaging And Digital Business Ecosystems
