A Model Based System Engineering (MBSE) and Probabilistic Assessment Approach for Additive Manufacturing (AM) Qualification

Abstract

Additive Manufacturing (AM) presents significant opportunities as an alternate source of supply within defense and aerospace sustainment; however, its integration into existing supply chains remains challenging due to fragmented qualification and certification processes. This thesis develops a Model-Based Systems Engineering (MBSE) and probabilistic assessment framework to standardize AM qualification within a digital materiel management environment. This research introduces a novel integration of MBSE with a Markov Decision Process (MDP) framework to model uncertainty and decision pathways for AM process qualification quantitatively. By embedding statistical and probabilistic reasoning into a Markov DecisionProcess (MDP) model, the proposed AM process qualification framework enables a consistent, data-driven approach that integrates AM part, material, and process qualification. The outcome supports decision-makers and stakeholders by providing a transparent, traceable, and model centric foundation for assessing AM performance-based qualification that meets airworthiness standards.