Date of Graduation

7-2021

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Engineering (PhD)

Degree Level

Graduate

Department

Industrial Engineering

Advisor/Mentor

Parnell, Gregory S.

Committee Member

Pohl, Edward A.

Second Committee Member

Goerger, Simon

Third Committee Member

LaScola Needy, Kim L.

Fourth Committee Member

Specking, Eric

Keywords

design maturation; multiobjective decision analysis; program management; set-based design; uncertainty reduction; unmanned aerial vehicle (UAV); value of information

Abstract

This dissertation comprises a body of research facilitating decision-making and complex system development with quantitative set-based design (SBD). SBD is concurrent product development methodology, which develops and analyzes many design alternatives for longer time periods enabling design maturation and uncertainty reduction. SBD improves design space exploration, facilitating the identification of resilient and affordable systems. The literature contains numerous qualitative descriptions and quantitative methodologies describing limited aspects of the SBD process. However, there exist no methodologies enabling the quantitative management of SBD programs throughout the entire product development cycle. This research addresses this knowledge gap by developing the process framework and supporting methodologies guiding product development from initial system concepts to a final design solution. This research provides several new research contributions. First, we provide a comprehensive SBD state-of-practice assessment identifying key knowledge and methodology gaps. Second, we demonstrate the physical implementation of the integrated analytics framework in a model-based engineering environment. Third, we develop a quantitative methodology enabling program management decision making in SBD. Fourth, we describe a supporting uncertainty reduction methodology using multiobjective value of information analysis to assess design set maturity and higher-resolution model usefulness. Finally, we describe a quantitative SBD process framework enabling sequential design maturation and uncertainty reduction decisions. Using an unmanned aerial vehicle case study, we demonstrate our methodology’s ability to resolve uncertainty and converge a complex design space onto a set of resilient and affordable design solutions.

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