Study of Data Structures and Tools for the Concurrent Conceptual Design of Complex Space Systems

Abstract

Concurrent design facilities are used by space agencies and private organizations to conduct preliminary design activities in the development of space systems. Concurrent conceptual design is characterized by dynamic exchanges between a limited team of experts, defining the operational requirements, the systems architecture, the baseline design, and budgets for different resources. The results are a preliminary system baseline and product requirements that are used as inputs to the subsequent product development phases. A study of the input and output of this early phase of product development has confirmed that data generated in concurrent design studies essentially describes behavior with a limited set of information about the geometry. The geometry at this stage is mainly composed of functional configurations with geometric envelopes. Based on this behavioral information content, the authors have looked at the SAPPhIRE model of causality, initially developed by Chakrabarti, as a potential data structure to support this early phase of system development and possibly all phases of the product lifecycle. In this current work, we present two concrete examples of concurrent conceptual design data structures for space applications and show how such data structures could be represented within the extended SAPPhIRE model. When compared to current PLM data structures, the use of the extended SAPPhIRE model represents an alternative means of structuring information and communicating this information between stakeholders, providing better understanding of the relation between a system's structure, function and behavior. It also explicitly represents the links between subsystems and the iterative nature of the design process.

A coordination method for concurrent design and a collaboration tool for parametric system models

“…The major differences are specialization on certain lifecycle phases and the focus and level of abstraction of parametric models. Fortin et al (2017) found out that only around 20% of the parameters in conceptual design describe geometry. Models used in the conceptual design of space systems primarily describe the system’s behavior; hence, tools deal little with geometry.…”

“…Such knowledge-based engineering approach is particularly advantageous when system designs can be generated based on models available for a product family (Prasad and Rogers, 2005). So far we did not include knowledge management capability into CEDESK, but we plan to add the possibility to store, search, and instantiate models from a component library as laid out in Fortin et al (2017).…”