A Functional Decomposition Approach for Feature-Based Reference Architecture Modeling Clemson University

Format:

Book

Conference/Event

Author/Creator:

St. Germain, Alessandra, author.

Contributor:

Colletti, Ryan

Paredis, Chris

Ahsan, Qamar

Rizzo, Denise

Conference Name:

SAE WCX Digital Summit (2021-04-13 : Live Online, Pennsylvania, United States)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2021

Summary:

Variant modeling techniques have been developed to allow systems engineers to model multiple similar variants in a product line as a single variant model. In this paper, we expand on this past work to explore the extent to which variant modeling in SysML can be applied to a broad range of dissimilar systems, covering the entire domain of ground vehicles, in single reference architecture model. Traditionally, a system's structure is decomposed into subsystems and components. However, this method is found to be ineffective when modeling variants that are functionally similar but structurally different. We propose to address this challenge by first decomposing the system not only by subsystem but also by high-level function. This pattern is particularly useful for situations where two variants perform the same function, but one variant performs the function using one subsystem, whereas the other variant performs the same function using one or more different subsystems. In our approach, two existing patterns, the encapsulation pattern and the 150% pattern, are slightly updated and combined. We demonstrate that by combining these two patterns, the opportunity for reuse of model elements is increased, which in turn decreases both the modeling time and likelihood of modeling mistakes. To demonstrate the functional decomposition pattern, a reference architecture model is presented that encompasses the full range of ground vehicles from traditional passenger cars to tracked military vehicles

Notes:

Vendor supplied data

Publisher Number:

2021-01-0259

Access Restriction:

Restricted for use by site license