Reliability Enhancement Decision Support System Tool for Small Satellites (REDS4)

Abstract

Small satellites are emerging as the new convenient means for developing countries, non-space specialized organizations, and educational institutions to pursue space missions. The utilization of small satellites is driven by the low cost of developing and launching, reduced development period, and simplicity in development compared to the larger satellites. Despite the gain in attention to small satellites by different entities, small satellites are becoming notorious for their low reliability and increased failure rate. The increased failure rate negatively impacts the space environment as the failed satellite becomes space junk, which poses a risk to other ongoing and future missions. The increased failure rate is attributed to development phase and utilization of Commercial of The Shelf Components(COTS) in design. Moreover, different organizations, such as the National Space and Aviation Administration (NASA) in the USA, are attempting to develop measures to improve small satellites' deteriorating reliability. In 2017, NASA started the Small Satellite Reliability Initiative to stimulate the space industry's contribution to improving small satellites' reliability. The initiative is still ongoing, and the space industry is searching for the best practices to ensure high-reliability missions. This thesis has been founded to contribute to the improvement of small satellites' reliability. The thesis tackles the reliability from the perspective of the of the decision-maker and aims to empower the developer with the tools to improve the design and selection of components. The thesis introduces a Reliability Estimation Framework that developers can use to estimate the reliability of COTS components. The framework utilizes the risks embedded within the operational environments to guide the developers to select the best components for their missions. The framework is coupled with the use of Decision Support Systems (DSS) to improve components' selection process. The DSS utilizes a multi-objective optimization process to optimize the selection of component combinations tailored based on the user requirements. The adaptation of the Reliability Estimation Framework and the DSS can enable the decision-makers to explore a wide range of component combinations that can deliver a successful mission at a reasonable cost. The output of the DSS is a Pareto curve of the feasible solutions. The solutions are presented mainly based on their cost and reliability. This is conducted to expand the decision-maker's options and provide them with the means to tradeoff in their decisions. Moreover, the utilization of the system results in a saving in costs, resources, time, and efforts.

Date of Award	May 2021
Original language	American English