AI-Enhanced TPS Development and Sustainment

LogiSys is proposing to transform the current process of Test Program Set (TPS) development from a document-based design and sustainment methodology to a model-based approach. While that alone can improve test fidelity and performance throughout the development process and improve sustainment, adding Artificial Intelligence (AI) and/or Automation can result in substantial time and cost savings throughout the TPS’s life cycle. Our process for validating this approach begins with standardizing Unit Under Test (UUT) and Automated Test Equipment (ATE) prerequisite documentation within the Model-Based Systems Engineering (MBSE) structure by creating or adopting a digital twin of both the UUT and ATE. AI tools and optimization algorithms will be evaluated and/or developed to assist throughout the TPS development process, including for test strategy development, model development and integration, and Test Program Hardware (TPH) design. These applications will then be integrated to work within the model to both extend the digital thread and produce the requisite design artifacts from the U.S. Army TPS development process. The key to the success of this proposal relies on the ability to develop a TPS digital twin while applying AI and/or algorithms to advance the TPS through each development phase.