Digital twin, a concept introduced in 2002, is becoming increasingly relevant to systems engineering and, more specifically, to model-based system engineering (MBSE). A digital twin, like a virtual prototype, is a dynamic digital representation of a physical system. However, unlike a virtual prototype, a digital twin is a virtual instance of a physical system (twin) that is continually updated with the latter’s performance, maintenance, and health status data throughout the physical system’s life cycle. This paper presents an overall vision and rationale for incorporating digital twin technology into MBSE. The paper discusses the benefits of integrating digital twins with system simulation and Internet of Things (IoT) in support of MBSE and provides specific examples of the use and benefits of digital twin technology in different industries. It concludes with a recommendation to make digital twin technology an integral part of MBSE methodology and experimentation testbeds.
As systems continue to grow in scale and complexity, the Systems Engineering community has turned to Model-Based Systems Engineering (MBSE) to manage complexity, maintain consistency, and assure traceability during system development. It is different from "engineering with models," which has been a common practice in the engineering profession for decades. MBSE is a holistic, systems engineering approach centered on the evolving system model, which serves as the "sole source of truth" about the system. It comprises system specification, design, validation, and configuration management. Even though MBSE is beginning to see a fair amount of use in multiple industries, specific advances are needed on multiple fronts to realize its full benefits. This paper discusses the motivation for MBSE, and its current state of maturity. It presents systems modeling methodologies and the role of ontologies and metamodels in MBSE. It presents model-based verification and validation (V&V) as an example of MBSE use. An illustrative example of the use of MBSE for design synthesis is presented to demonstrate an important MBSE capability. The paper concludes with a discussion of challenges to widescale adoption and offers promising research directions to fully realize the potential benefits of MBSE.
K E Y W O R D Smodel-based systems engineering (MBSE), modeling and simulation, system integration, systemsof-systems, verification and validation
As systems are called on to participate on demand within system‐of‐systems (SoS), system‐of‐systems integration (SoSI) has become a key concern. This capability is especially important in defense and aerospace where systems are increasingly required to interoperate on demand to satisfy mission requirements. SoSI is also becoming increasingly important in healthcare and energy domains. SoSI involves interfacing and enabling the interactions of component systems to create the needed SoS capability to accomplish mission or business goals. SoSI, which is part of the overall SoS development life cycle, increases in complexity when there are legacy systems that need to be integrated, and when humans are tasked to perform in various capacities within the SoS. An added layer of complexity is introduced when the SoS has to exhibit certain quality attributes such as adaptability and resilience in the face of contingencies and disruptions in the operational environment. This paper addresses key considerations and challenges in SoSI.
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