Optimal bivariate mission abort policy for systems operate in random shock environment

For many safety-critical systems such as aircrafts, nuclear power plants and human space flights, system survival has higher priority over mission completion. For the purpose of enhancing the survivability of safety-critical systems, a mission can be aborted when a certain malfunction condition is satisfied and a rescue procedure is initialized immediately. As the configuration and operating environment for most mission-oriented systems are becoming increasingly complex, multiple failure criteria are commonly observed. This paper investigates the optimal mission abort policy for systems executing missions in a random environment combining cumulative shock model and run shock model. The mission is aborted when the cumulative number of valid shocks reaches a critical value or the number of consecutive valid shocks exceeds a preset level. Under the proposed bivariate mission abort policy, mission success probability and system survivability are evaluated. Two optimization models are constructed to minimize the expected total cost and maximize the mission success probability while providing a desired system survivability. In addition, two heuristic abort policies that only consider single abort criterion are illustrated to justify the advantage of the constructed bivariate mission abort policy. A case study on an aircraft performing transportation task is presented to illustrate the obtained results.

Automated summary

This paper investigates the optimal mission abort policy for systems executing missions in a random environment combining cumulative shock model and run shock model. Two optimization models are constructed to minimize the expected total cost and maximize the mission success probability while providing a desired system survivability. The advantages of the constructed bivariate mission abort policy are justified through two heuristic abort policies that only consider single abort criterion.