Towards Polymorphic Systems Engineering - Mathieson, John T.J. (The George Washington University, 2021)
Systems engineering is widely regarded as a full life cycle discipline and provides methodologies and processes to support the design, development, verification, sustainment, and disposal of systems. While this cradle-to-grave concept is well documented throughout literature, there has been recent and ever-increasing emphasis on evolving and digitally transforming systems engineering methodologies, practices, and tools to a model-based discipline, not only for advancing system development, but perhaps more importantly for extending agility and adaptability through the later stages of system life cycles – through system operations and sustainment. This research adopts principles from the software engineering domain DevOps concept (a collaborative merger of system development and system operations) into a Systems Engineering DevOps Lemniscate life cycle model. This progression on traditional life cycle models lays a foundation for the continuum of model-based systems engineering artifacts during the life of a system and promotes the coexistence and symbiosis of variants throughout. This is done by facilitating a merger of model-based systems engineering processes, tools, and products into a surrogate and common modeling environment in which the operations and sustainment of a system is tied closely to the curation of a descriptive system model. This model-based approach using descriptive system models, traditionally leveraged for system development, is now expanded to include the operational support elements necessary to operate and sustain the system (i.e. executable procedures, command scripts, maintenance manuals, etc. modeled as part of the core system). This evolution on traditional systems engineering implementation, focused on digitally transforming and enhancing system operations and sustainment, capitalizes on the ability of model-based systems engineering to embrace change to improve agility in the later life cycle stages and emphasizes the existence of polymorphic systems engineering (performing a variety of systems engineering roles in simultaneously occurring life cycle stages to increase system agility). A model-based framework for applying the Systems Engineering DevOps life cycle model is introduced as a new Systems Modeling Language profile. A use-case leveraging this “Model-Based System Operations” framework demonstrates how merging operational support elements into a spacecraft system model improves adaptability of support elements in response to faults, failures, and evolving environments during system operations, exemplifying elements of a DevOps approach to cyber-physical system sustainment.