Dissertation/Thesis Abstract

Finding Determinants for Optimizing System Development Planning and Acquisition Strategies Using Linear Discriminant Analysis
by Mills, Hugh E., Jr., D.Engr., The George Washington University, 2018, 51; 10743269
Abstract (Summary)

Complexity in systems acquisition can be characterized by descriptors in a system’s architecture that portray interrelationships and interdependencies, technology readiness levels, test and evaluation, integration, and technical requirements, lifecycle support and other factors. Well known resource estimating measures such as mass, power, fuel requirements, etc. can be added to achieve a multivariable description of a desired program. Seldom can all these contributors to a system development and procurement plan be accommodated, optimized, or even known. There is no set of guidelines in this environment to select the best development and acquisition strategy. This paper attempts to begin mapping acquisition strategies and system planning paradigms to system performance indicators, with the intent of providing guidelines for future complex system efforts. Since the acquisition strategies and system planning paradigms are themselves complex, they are accepted as non-ordinal categorical variables in this analysis. An attempt is made to match them against empirical program performance indicators for cost and schedule using the technique of linear discriminant analysis with NASA mission data as the complex systems. While the results do not yield a significant determinant of optimum acquisition program strategy, there is evidence of separation in one set of category groupings that invites future research.

Indexing (document details)
Advisor: Doskey, Steven, Moreland, James D., Jr.
Commitee: Doskey, Steven, Etemadi, Amir, Hunt, Charles D., Moreland, Jr., James D., Murphree, E. Lile
School: The George Washington University
Department: Engineering Management
School Location: United States -- District of Columbia
Source: DAI-B 79/07(E), Dissertation Abstracts International
Source Type: DISSERTATION
Subjects: Management, Engineering, Systems science
Keywords: Data analysis, Discriminant analysis, Multivariate analysis, Program management, Project management, Space technology
Publication Number: 10743269
ISBN: 9780355614251
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