PhD Defense by Kevin Reilley
(Advisor: Prof. Mavris)
Will defend a doctoral thesis entitled,
P-SEMP: A Platform for Systems Engineering Modeling and Planning
Tuesday, December 8, 2020 at 3:00 p.m.
Systems engineering management and planning has long been a realm dominated by arcane standards, by the weight of years of practice, and by authority. However, with technological advances and the desire to solve socio-technical problems at the level of increasingly complex systems, authority alone is no longer sufficient for the justification of systems engineering practice. As new methodologies are bought and sold in the transition towards model-based systems engineering, there is an imperative for the systems engineering practitioner to develop new techniques for estimating project performance before project completion. That is, whether debating appropriate corrective actions for a project at risk of going over budget or over schedule, or when planning a new systems engineering methodology, the systems engineer must forecast planned performance of systems engineering tasks. To this end, the International Council of Systems Engineers (INCOSE) and others have sought to bolster systems engineering measurement and the development of standardized leading indicators of systems engineering performance, which are thought to give insight into future performance in the course of program performance. Recent efforts have produced models of systems engineering performance; however, no model is yet sufficient for addressing which tasks in support of standardized processes should be planned in a systems engineering methodology. This thesis seeks to address this shortfall by constructing a platform for the numerical comparison of systems engineering methodology.
In summation, a leading indicator model is replicated and found wanting. Systems engineering method model simulations are formulated for validation tasks, and a domain-specific language is created to capture them in the system model for exploration of task architecture. Finally, broader description of designs of experiments and probability are incorporated to improve analytical integration capabilities required for full validation activities. Altogether, these pieces outline a platform for systems engineering modeling and planning on the basis of constructing the platform through various models and exercising the platform, improving systems engineering methodology analysis.
- Prof. Dimitri N. Mavris – School of Aerospace Engineering (advisor)
- Prof. Daniel P. Schrage – School of Aerospace Engineering
- Prof. Eric M. Feron – School of Aerospace Engineering
- Dr. Alicia Sudol – School of Aerospace Engineering
- Dr. Russell S. Peak – School of Aerospace Engineering
- Dr. Bjorn F. Cole – Lockheed Martin