Mastering SoS complexity through a methodical tailoring of modeling: Benefits and new issues

Abstract

The complexity of systems like Systems of Systems leads to very time-consuming modeling tasks. Standards such as modeling languages, frameworks, etc. have been developed by organizations to master this complexity. Although they are useful, almost mandatory, having them systematically as the entry point of modeling adds new complexity challenges causing additional costs in Systems Engineering activities. An automated objective-driven approach named Modeling Planning Process (MPP) that drives the usage of such standards has been proposed to master the modeling activities. Its application in actual projects to tailor the modeling effort, clearly demonstrated its relevance. The result is that tailoring modeling is mandatory, thus modeling choices (framework, models, etc.) are based and assessed against previously defined modeling objectives (MOs). This paper firstly summarizes the MPP approach we extended and automated recently; a five-step approach based on MOs as entry points that drive modeling activities. Secondly, the effectiveness of the approach is demonstrated through a case study that exposes two simple MOs and the conceptual data model to support them. This experience shows that the modeling effort should be tailored according to two perspectives: what must be modeled, and how far this modeling must be performed. Finally, the paper presents the induced necessity for a formal approach to federate models.