NASA’s long-term goals include dramatic reductions in the cost of space transportation. Achieving this goal requires innovative technologies and new approaches to vehicle design, development, manufacturing, and operation. Among the innovations needed is the development of design assessment models that enable the analysis of all life cycle activities for space transportation system concepts, from development to operations.

Operations models (ground operations or spaceport operations) are an important part of the assessment of new vehicle architectures since they reflect a large portion of the system’s recurring costs and will determine the vehicle flight rate capability. The recurring costs and the flight rate are the result of tasks or activities that are required during ground operation (for example, the preparation of a payload for integration with the vehicle). Typically the cost and task duration assessments of these processes are performed by experienced engineers who employ their knowledge of production and operations technology, methods analysis, and engineering economics to predict the probable cost and production time of a product – in this case a ground operation activity.

This research focuses on the development and evaluation of new techniques for automating the operations assessment of future space transportation systems by using a combination of activity-based costing and simulation modeling. The approach translates vehicle design parameters into a set of activities and a related process map in a domain (operations characteristics of future space vehicle concepts) where there is limited knowledge. This approach is innovative because it will, for the first time, combine activity-based cost modeling (which is known to work well in well-defined environments) with expert knowledge to estimate the activities, cost, and time characterizations associated with proposed space transportation concepts. A critical element of this research is the gathering of data and expert opinions in order to develop “knowledge engines” for major vehicle subsystems. The knowledge engines capture existing and futuristic approaches to a vehicle subsystem and link those to an activity set, time, cost, failure characterizations, and process map.

Key accomplishments:

• Created the initial framework for the knowledge engines.
• Developed a preliminary knowledge engine for the Thermal Protection Systems (TPS).
• Prepared an initial prototype tool to support the process of “knowledge capturing.”

Key milestones:

• Complete the knowledge engine for TPS.
• Develop a working tool that automates the translation of design variables into activities and process map using the developed TPS knowledge engine.
• Create a knowledge engine for a second subsystem.
• Integrate the second knowledge engine into the working tool.

Contact: E. Zapata (Edgar.Zapata-1@ksc.nasa.gov), YA-D4, (321) 867-6234
Participating Organization: University of Texas El Paso (Dr. A. Ruiz-Torres) and Command and Control Technologies Corp.