Optimal aborting in cumulative parallel missions with individual and common shocks

Mission systems (e.g., drones, aircraft) often operate in random shock environments. Existing reliability studies have mostly assumed either individual or common shock processes, which may deteriorate a single component or multiple components simultaneously. This paper advances the state of the art by modeling a mission system with multiple components that undergo both individual and common shocks, operating in parallel and contributing cumulatively to the mission success. To avoid excessive components losses, a shock-based, interval-dependent abort policy is proposed and designed to minimize the expected mission losses (EML). A new numerical procedure is put forward to assess the mission success probability and the expected number of lost components, which are then used to determine the EML. Based on the EML evaluation and a suggested string solution representation, the genetic algorithm is implemented to solve the EML minimization problems under fixed and dynamic possible aborting times (PAT). A detailed case study of a multi-drone target destruction mission system is conducted to demonstrate the proposed model. The impacts of several model parameters (mission failure penalty, common shock rate, number of system components, and number of PAT) on mission performance metrics and optimization solutions are also investigated.