Requirements Controlled Design: A Method for Discovery of Discontinuous System Boundaries in the Requirements Hyperspace

Decision making;Requirements;Complex systems;Aerospace design

Hollingsworth, Peter Michael ; Aerospace Engineering

University:Georgia Institute of Technology

Department:Aerospace Engineering

关键词: Decision making;    Requirements;    Complex systems;    Aerospace design;   

Others  :  https://smartech.gatech.edu/bitstream/1853/5197/1/hollingsworth_peter_m_200405_phd.pdf

美国|英语

来源: SMARTech Repository

【 摘 要 】

The drive toward robust systems design, especially with respect to system affordablility throughout the system life-cycle, has led to the development of several advanced design methods. While these methods have been extremely successful in satisfying the needs for which they have been developed, they inherently leave a critical area unaddressed. None of them fully considers the effect of requirements on the selection of solution systems. The goal of all of current modern design methodologies is to bring knowledge forward in the design process to the regions where more design freedom is availableand design changes cost less. Therefore, it seems reasonable to consider the point in the design process where the greatest restrictions are placed on the final design, the point in which the system level requirements are set. Historically the requirements have been treated as something handed down from above. However,neither the customer nor the solution provider completely understood all of the options that are available in the broader requirements space. If a method were developed that provided the ability to understand the full scope of the requirements space, it would allow for a better comparison of potential solution systems with respect to both the current and potential future requirements. The key to a requirements conscious method is to treat requirements differently from the traditional approach. The method proposed herein is known as Requirements Controlled Design (RCD). By treating the requirements as a set of variables that control the behavior of the system, instead of variables that only define the response of the system, it is possible to determine a-priori what portions of the requirements space that any given system is capable of satisfying. Additionally, it should be possible to identify which systems can satisfy a given set of requirements and the locations where a small change in one or more requirements poses a significant risk to a design program. This thesis puts forth the theory and methodology to enable RCD, and details and validates a specific method called the Modified Strength Pareto Evolutionary Algorithm (MSPEA).