Date of Award

Spring 5-2017

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Computing

School

Computing Sciences and Computer Engineering

Committee Chair

Zheng Sun

Committee Chair Department

Computing

Committee Member 2

Andrew Strelzoff

Committee Member 3

Chaoyang Zhang

Committee Member 3 Department

Computing

Committee Member 4

Zheng Wang

Committee Member 5

Nan Wang

Committee Member 5 Department

Computing

Abstract

The goal of robust design is to select a design that will still perform satisfactorily even with unexpected variation in design parameters. A resilient design will accommodate unanticipated future system requirements. Through studying the variations of system parameters through the use of multi objective optimization, a designer hopes to locate a robustly resilient design, which performs current mission well even with varying system parameters and is able to be easily repurposed to new missions. This ability to withstand changes is critical because it is common for the product of a design to undergo changes throughout its life cycle. This subject has been an active area of research in industrial design and systems engineering but most methodologies rest upon exhaustive understanding of design, manufacturing and mission variance. The thrust of this research is to develop new methodologies for estimating robust resilience given imperfect information. In this work we will apply new methodologies for locating resilient designs within a dataset derive from a study performed by the Small Surface Combatant Task Force in order to improve upon a state of the art design process. Two new methodologies, permutation stability analysis and mutation stability analysis, are presented along with results and discussion as applied to the SSCTF dataset. It is demonstrated that these new methods improve upon the state of the art by providing insight into the robustness and resilience of selected system properties. These methodologies, although applied to the SSCTF dataset are posed more generally for wider application in system design.

ORCID ID

0000-0001-6452-8398

Share

COinS