Degree Type


Date of Award


Degree Name

Master of Science


Industrial and Manufacturing Systems Engineering

First Advisor

Paul J. Componation

Second Advisor

Caroline C. Krejci


A recognized issue related to the processes in systems engineering is that they vary based on the project and organization. However, understanding how to tailor the systems engineering processes to help ensure project success continues to trouble engineers, and practical tools to help aid engineers in this field are not as readily available as many would like. Moreover, budget and schedule constraints continue to place an additional burden on systems engineering being done well. Many studies on how to help contribute to improving systems engineering exists for different organizations. Yet, most studies are based on case studies from one project, involve a small sample size, or only focus on one organization type. This thesis discusses the results of how systems engineering processes applied to complex projects impact project success based on organization type with a sample size of 180 institutions. The organizations examined are divided into two groups, commercial organizations and government organizations. Within the commercial organization, government-focused projects and commercial-focused projects are examined. Within the government organization, projects from the National Aeronautics and Space Administration (NASA) Agency are examined. NASA is a government organization comprised of 10 Centers located around the country, and for the purpose of this research, is the primary organization discussed and metric in which the other organizations will be quantitatively compared and contrasted against. For this reason, the standard participants used in this research effort were NASA's 17 systems engineering processes. Data was gathered through a modified data collection instrument, and a three-level data analysis was performed. First, meaningful correlations were identified between the systems engineering processes and project success metrics, as well as, non-technical variables and project success metrics for the different organizations. Then, a deeper data analysis was conducted to test for statistically significant differences through project description variables, project success metrics, and systems engineering processes across organization types. Finally, statistically significant differences among the project description variables, project success metrics, systems engineering processes, and non-technical variables were examined within each organization type. The results from the data analysis will be delivered to NASA to help aid in the development of a NASA systems engineering practitioners guide.


Copyright Owner

Kathryne Angela Schomburg



File Format


File Size

146 pages

Included in

Engineering Commons