Optimal Mission Abort Decisions for Multi-Component Systems Considering Multiple Abort Criteria

Xiaofei Chai, Boyu Chen and Xian Zhao ()
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Xiaofei Chai: School of Management and Economics, Beijing Institute of Technology, Beijing 100081, China
Boyu Chen: Brandeis International Business School, Brandeis University, Waltham, MA 02454, USA
Xian Zhao: School of Management and Economics, Beijing Institute of Technology, Beijing 100081, China

Mathematics, 2023, vol. 11, issue 24, 1-12

Abstract: This paper studies the optimal mission abort decisions for safety-critical mission-based systems with multiple components. The considered system operates in a random shock environment and is required to accomplish a mission during a fixed mission period. If the failure risk of the system is very high, the main mission can be aborted to avoid higher failure cost. The main contribution of this study lies in the design and optimization of mission abort policies for multi-component systems with multiple abort criteria. Moreover, multi-level transitions are considered in this study to characterize the different shock-resistance abilities for components in different states. Mission abort decisions are determined based on the number of components in either defective or failed state. The problem is formulated in the framework of the finite Markov chain imbedding method. We use the Monte-Carlo simulation method to derive the mission reliability and system survivability. Numerical studies and sensitivity analysis are presented to validate the obtained result.

Keywords: mission abort; system survivability; multi-component system; mission reliability (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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