Model Based Digital Engineering: Accelerating Digital Transformation through Integrated Data and Model Management Framework

Abstract

The increasing complexity of engineered systems and the demand for rapid innovation are straining traditional, siloed engineering practices. Despite the adoption of digital tools, many organizations suffer from fragmented environments, leading to inefficiencies, communication failures, and recurring challenges with project cost, scheduling, and design validation. To address these issues, this thesis introduces a comprehensive framework for Model-Based Digital Engineering (MBDE) designed to unify disparate systems into a cohesive digital ecosystem. Central to this is a vendor-neutral architecture that treats data and models as core enterprise assets. Recognizing that many digital transformations stall due to a lack of data and model governance, the proposed framework establishes the essential architectural, procedural, and governance mechanisms for a scalable MBDE implementation, enabling seamless traceability and consistency. By bridging the gap between strategy and execution, this work offers an actionable methodology for transitioning to an integrated, model-based enterprise. The results underscore that structured data interoperability, cross-disciplinary collaboration, and lifecycle model continuity are critical for achieving measurable gains in engineering efficiency, program agility, and system performance.