Application of artificial intelligence (AI) concepts to the development of space flight parts approval model

摘要

The National Aeronautics & Space Administration (NASA), and the European Space Agency (ESA) missions involves the performance of scientific experiments in Space. To perform these experiments, instruments are designed, developed, built, and launched. The Instruments are fabricated using many electronic parts. For Instruments to perform reliably for the specified duration of the mission, the selection of commercial parts must be monitored and strictly controlled. NASA's process to achieve this goal is by the review and approval of commercial parts used to build the Instrument. ESA also follows a similar process although some requirements are different. The present system to select and approve parts for space applications is very inefficient, manual, inconsistent, slow and tedious, and very costly. This paper presents a cost-effective, accurate, and consistent model which uses the artificial intelligence techniques in the selection and approval of parts. The knowledge which is acquired from the specialists for different part types are then represented in a knowledge base in the form of ules and objects. The parts information is stored separately in a database and is isolated from the knowledge base for ease of maintenance. Validation, verification, and performance issues as well as other implementation details are highlighted.