Pluggable analysis viewpoints for design space exploration

Viewpoint modeling is an effective approach for analyzing and designing complex systems. Splitting various elements and corresponding constraints into different perspectives of interests, enables separation of concerns such as domains of expertise, levels of abstraction, and stages in lifecycle. Specifically, in Systems Engineering different viewpoints could include functional requirements, physical architecture, safety, geometry, timing, scenarios, etc. Despite partial interdependences, the models are usually developed independently by different parties, using different tools and languages. However, the essence of Systems Engineering requires repetitive integration of many viewpoints in order to find feasible designs and to make good architectural decisions, e.g., in each mapping between consecutive levels of abstraction and in each design space exploration. This integration into one consistent model becomes a significant challenge from both modeling and information management perspectives. In this paper we suggest (1) a unique modular algebraic viewpoint representation robust to design evolution and suitable for generation of the integrated optimization/analysis models, and (2) an underlying ontology-based approach for consistent integration of local viewpoint concepts into the unified design space model. We show an example of an optimization model with different combinations of partially interdependent Analysis Viewpoints. Using the proposed modeling and information management approaches the underlying viewpoints equations can be applied without modification, making the approach pluggable.