Bringing Legacy Technical Data out of the Shadows Using Modern Digital Enginering Tools

Model-Based Systems Engineering (MBSE) and Digital Engineering (DE) are poised to significantly transform the automated test sector. However, the broad integration of these principles is hindered by issues related to the completeness and uniformity of existing technical data. Organizations responsible for automated test systems are often dependent of a diverse array of test requirement documents, ranging from military to contractor standards, with some legacy documents not adhering to any recognized standard or being entirely unavailable. There is a pressing need for mechanisms that can facilitate the transition from these varied legacy formats to contemporary digital engineering tools. This paper proposes a comprehensive strategy and a tooling framework designed to convert a wide range of legacy documents into a unified XML-based model format. It outlines various use cases and tooling frameworks, along with their foundational methodologies. Additionally, the paper examines the effects on the standard timelines for Test Program Set Development and proposes a structure for future innovations that leverage machine learning and artificial intelligence to address some of the sector's most challenging issues. Leveraging artificial intelligence is a key enabler for many of the "legacy document to XML" translation tools presented. Modern Large Language Models (LLM) can recognize patterns in test requirements and discern meaning from the placement of data within a table or flow chart. This is powerful because it can drastically improve the quality and speed at which legacy documents are converted from PDF format to the model-based eXtensible Markup Language (XML) formats like IEEE ATML 1671. When test requirements are clearly defined upfront and not hidden from the engineering organization in legacy documents engineering managers, customers and developers can all better support the end users with accurate and faster Test Program Set development. With models in hand test asset managers will have the luxury of managing obsolescence in automated test equipment by replacing system components with instruments that meet the original Unit Under Test (UUT) requirements rather than continuously replacing instruments with comparable or better instruments in every category to ensure backwards compatibility. This often drives the cost of automated test equipment up drastically compared to the actual need and is particularly an issue when automated test equipment has been refreshed several times and supports hundreds or thousands of legacy tests.