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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Advisor: Prof. Dimitri N. Mavris
Committee Members:
Dr. Jean Charles Domercant
Professor Dimitri Mavris
Professor Daniel Schrage
Methodology to Identify Flexible Product Architectures
ABSTRACT:
The use of unmanned aerial vehicles (UAVs) is becoming widespread across government, military, and will soon be integrated in civil operations. Also, in today's budgetary environment, manufacturers are under increasing pressure to develop cost-effective, timely products. Even though UAVs are a relatively new industry, they are beginning to feel the same fiscal pressures. Due to multi-mission, capability-based design requirements and tighter fiscal constraints, system architects use reconfigurable or product family architectures in order to increase performance capabilities or reduce manufacturing costs. The introduction of new architectures results in increased complexity. Depending on the industry different product architectures are preferred, but because the UAV industry is emerging, it is laborious to determine which architecture should be implemented. Therefore, correctly selecting an initial product architecture to meet present and future requirements is required. Consequences of inadequate product architecture implementation include sub-optimal performance, cost overruns, loss of customers, and possible restart or scrapping of the product's production. Therefore, this dissertation proposes a method that aids the system architect in choosing the most appropriate product architecture when developing vehicles and planning their evolution.
The proposed method identifies architecture selection drivers, creates a numerical architecture space, and develops evaluation criteria. Drivers are derived from case studies of multiple industries, and validated with sensitivity studies. Historical data is collected to determine the drivers' impact. Commonality and re-configurability indexes from previous product design methods are used to numerically represent the architecture space. Finally, in order to capture the trade-off between requirement satisfaction and flexibility of a product architecture, new metrics are introduced that capture an architecture's ability to satisfy given requirements, resilience to changing requirements, and difficulty to be modified. The result provides system architects means to identify favorable product architectures by using existing multi-attribute decision making (MADM) methods to make the final decision.
If successful, the method can aid system architects in determining the most feasible architecture evolutionary path, performing trade-offs between different architecture alternatives, and identifying relations among a system architecture and its production. Execution of the method occurs before down-selecting configuration during conceptual design and is designed to increase traceability of the decisions made throughout the rest of the design process.
