Trade-space exploration analysis for a system incorporating parametric cost mathematical models: a case study of satellite anomalies

Abstract—Satellites are essential for modern applications such as communication, navigation, and Earth observation. However, their operation in the harsh conditions of space makes them susceptible to anomalies and failures, leading to significant operational and financial losses. This research aims to address these challenges by identifying recurring satellite problems, optimizing the trade-offs between cost, design life, insurance loss, and performance using trade-space exploration analysis to improve satellite reliability and cost-effectiveness. The satellite anomalies that are considered in this research are antenna, payload, attitude control system, and power system. These four anomalies are selected based on the most failed subsystems from the Seradata database. Parametric cost models: Exponential and Weibull are analyzed using the trade-space exploration (TSE) technique, focusing on selecting the best design option to minimize failures and associated costs, including launch expenses and insurance losses. The performance of each model is compared using Root Mean Square Error (RMSE). From the results, it can be deduced that the Exponential model has the lowest RMSE value for each component. The RMSE values of the Exponential model are much lower with cost versus design life values of 42.21, 59.88, 31.27, and 32.00 compared to the Weibull model’s values of 226.54, 255.30, 316.75, and 217.83, respectively. The findings highlight the key factors contributing to satellite anomalies and demonstrate how the developed models can guide decision-making in satellite design and operations. By balancing cost, performance, and design life, this research provides valuable insights for designing cost-effective satellites while enhancing their operational success.