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Failure risk management: adaptive performance control and mission abort decisions
Qingan Qiu1, Rong Li2, Xian Zhao2,3
1School of Management, Beijing Institute of Technology, Beijing, China.
Summary
This study introduces dynamic performance control and mission abort (PCMA) for safety-critical systems. Optimized PCMA decisions maximize revenue by balancing mission success and failure risk.
Area of Science:
- Engineering
- Operations Research
- Risk Management
Background:
- Safety-critical systems' failure risk is linked to performance levels, offering control opportunities.
- Mission abort is a key strategy for mitigating hazards during operations.
Purpose of the Study:
- To maximize expected revenue by optimizing dynamic performance control and mission abort (PCMA) decisions.
- To balance mission completion probability with system failure risk in successive missions.
Main Methods:
- Formulated the joint optimization problem as a Markov decision process for condition-based PCMA.
- Established monotonicity and concavity of the value function to derive optimal policies.
- Analyzed heuristic policies for comparative performance evaluation.
Main Results:
- Optimizing mission abort policies requires a series of control limits.
- Identified conditions for monotone performance control policies.
- Demonstrated the superiority of proposed risk control policies in a UAV power line inspection case study.
Conclusions:
- Dynamic performance adjustment and mission abort decisions enhance operational performance and rewards for safety-critical systems.
- The proposed PCMA framework effectively reduces failure risk while increasing operational rewards.
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