Date of Award

January 2015

Degree Type

Thesis

Degree Name

Master of Science in Aeronautics and Astronautics

Department

Aeronautics and Astronautics

First Advisor

Daniel A DeLaurentis

Committee Member 1

Jitesh Panchal

Committee Member 2

Robert C Kenley

Committee Member 3

Nathan Hartman

Abstract

As design teams are becoming more globally integrated, one of the biggest challenges is to efficiently communicate across the team. The increasing complexity and multi-disciplinary nature of the products are also making it difficult to keep track of all the information generated during the design process by these global team members. System engineers have identified Model-based Systems Engineering (MBSE) as a possible solution where the emphasis is placed on the application of visual modeling methods and best practices to systems engineering (SE) activities right from the beginning of the conceptual design phases through to the end of the product lifecycle. Despite several advantages, there are multiple challenges restricting the adoption of MBSE by industry. We mainly consider the following two challenges: a) Industry perceives MBSE just as a diagramming tool and does not see too much value in MBSE; b) Industrial adopters are skeptical if the products developed using MBSE approach will be accepted by the regulatory bodies. To provide counter evidence to the former challenge, we developed a generic framework for translation from an MBSE tool (Systems Modeling Language, SysML) to an analysis tool (Agent-Based Modeling, ABM). The translation is demonstrated using a simplified air traffic management problem and provides an example of a potential quite significant value: the ability to use MBSE representations directly in an analysis setting. For the latter challenge, we are developing a reference model that uses SysML to represent a generic infusion pump and SE process for planning, developing, and obtaining regulatory approval of a medical device. This reference model demonstrates how regulatory requirements can be captured effectively through model-based representations. We will present another case study at the end where we will apply the knowledge gained from both case studies to a UAV design problem.

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