Mission Abort Policy for Systems with Observable States of Standby Components

For some critical applications, successfully accomplishing the mission or surviving the system through aborting the mission and performing a rescue procedure in the event of certain deterioration condition being satisfied are both pivotal. This has motivated considerable studies on mission abort policies (MAPs) to mitigate the risk of system loss in the past several years, especially for standby systems that use one or multiple standby sparing components to continue the mission when the online component fails, improving the mission success probability. The existing MAPs are mainly based on the number of failed online components ignoring the status of the standby components. This article makes contributions by modeling standby systems subject to MAPs that depend not only on the number of failed online components but also on the number of available standby components remaining. Further, dynamic MAPs considering another additional factor, the time elapsed from the mission beginning in the event of the mission abort decision making, are investigated. The solution methodology encompasses an event-transition based numerical algorithm for evaluating the mission success probability and system survival probability of standby systems subject to the considered MAPs. Examples are provided to demonstrate the benefit of considering the state of standby components and elapsed operation time in obtaining more flexible MAPs.     

Optimal Abort Rules for Multiattempt Missions

Many real‐world systems use mission aborts to enhance their survivability. Specifically, a mission can be aborted when a certain malfunction condition is met and a risk of a system loss in the case of a mission continuation becomes too high. Usually, the rescue or recovery procedure is initiated upon the mission abort. Previous works have discussed a setting when only one attempt to complete a mission is allowed and this attempt can be aborted. However, missions with a possibility of multiple attempts can occur in different real‐world settings when accomplishing a mission is really important and the cost‐related and the time‐wise restrictions for this are not very severe. The probabilistic model for the multiattempt case is suggested and the tradeoff between the overall mission success probability (MSP) and a system loss probability is discussed. The corresponding optimization problems are formulated. For the considered illustrative example, a detailed sensitivity analysis is performed that shows specifically that even when the system's survival is not so important, mission aborting can be used to maximize the multiattempt MSP.     

Optimal Mission Abort Policy for Systems Operating in a Random Environment

Many real‐world critical systems, e.g., aircrafts, manned space flight systems, and submarines, utilize mission aborts to enhance their survivability. Specifically, a mission can be aborted when a certain malfunction condition is met and a rescue or recovery procedure is then initiated. For systems exposed to external impacts, the malfunctions are often caused by the consequences of these impacts. Traditional system reliability models typically cannot address a possibility of mission aborts. Therefore, in this article, we first develop the corresponding methodology for modeling and evaluation of the mission success probability and survivability of systems experiencing both internal failures and external shocks. We consider a policy when a mission is aborted and a rescue procedure is activated upon occurrence of the m th shock. We demonstrate the tradeoff between the system survivability and the mission success probability that should be balanced by the proper choice of the decision variable m . A detailed illustrative example of a mission performed by an unmanned aerial vehicle is presented.