Digital Engineering changes the way organizations conceive, design, manufacture, deploy, sustain and retire products. This enables engineers across different domains to effectively and efficiently communicate design intent, identify emergent behaviors of complex systems, and perform advanced trade studies, multi-domain analyses and optimization that provides stakeholders with the right information at the right time in the right format.
One of the core capabilities of Digital Engineering is the concept of a Digital Twin. A Digital Twin serves as a digital replica of an as-built, physical system that includes realistic replication of structural, behavioral and performance characteristics through models that are correlated with and corrected by field data from the physical system and data backhaul. As part of SAIC’s investment as a leader in the development and implementation of Digital Engineering solutions, a demonstration of a Digital Twin application was completed for an example space exploration program. This presentation provides an overview of this program’s design and development as it was completed using the Digital Engineering Framework to create an exemplar Digital Twin.
Digital Engineering requires a cultural change to engineering practices, particularly for large aerospace and defense programs. Delivering performance at the speed of relevance requires fundamental changes to how organizations acquire and develop technology. These fundamental changes accelerate technical integration and progression by consolidating and connecting once isolated data, exposing it to the entire multi-disciplinary development team, and storing it for future reference. Enabling availability of the right data at the right time in a meaningful format leads to more efficient communications, automation of tasks as updates occur, reduced defects, reduced rework, improved system integration and faster time to initial operating capability.
SAIC’s Digital Engineering capabilities consist of five core thrust areas: Model Based System Engineering (MBSE), Digital Thread Development, Digital Twin Frameworks, Tool Federation with a Semantic Data Broker, and Digital Engineering Ecosystems. A team within the SAIC Digital Engineering Innovation Factory recently undertook an internally funded project to demonstrate a Digital Twin based on a mock product, the Lunar Landscape Lighting unit, as an example complex space exploration project. The small team consisted of multi-disciplinary engineers and scientists that had access to off-the-shelf software packages and were assigned the primary objective to demonstrate the implementation of a digital engineering framework. This presentation will be a summary of SAIC’s program as-executed and demonstrate how the digital engineering framework was used to construct engineering artifacts across multiple domains connected by the digital thread thus enabling on-demand requirement change impacts, exploring design what-ifs, and inspiring collaboration across the team through implementing a Digital Twin.
For the Lunar Landscape Lighting program (also referred to as Tri-Ell), the multi-disciplinary team utilized tools from the SAIC digital engineering ecosystem to develop models and analyses needed to address the program requirements. Using an agile process, the team carried out design sprints to develop solutions and perform trade studies. As the program progressed, the team also created physical prototypes and utilized sensors and feedback mechanisms to the modeling environment to create and validate the Digital Twin. The team was able to exercise design changes and what-if scenario execution with the Digital Twin, as well as provide real time data displaying to an Internet of Things (IoT) dashboard. Additionally, the team made use of Virtual Reality (VR) and Mixed Reality environments together with the Digital Twin to explore the design space, monitor operations, and better understand constraints and user needs.
This summary presentation of the Tri-Ell program will demonstrate the use and value of a Digital Twin for complex systems.