Abstract
Modern smart products are endowed with the capability to autonomously repair damage from random shocks, thereby highlighting the critical necessity to incorporate this self-healing attribute in reliability assessments. This paper investigates periodically inspected self-healing systems that are exposed to dependent competing failure processes within dynamically evolving environments. The impact of environmental changes is manifested in that both the natural degradation process and the self-healing behavior are governed by distinct laws in varying environments. Explicit formulas for the system reliability and availability are analytically derived using the stochastic process theory, and their correctness is verified by proposed simulation algorithms respectively. Meanwhile, the inspection period is optimized by minimizing the long-run average cost rate. Lastly, a practical example of semiconductor lasers is applied to showcase the application of the presented methods. The sensitivity analysis reveals that increasing the self-healing time threshold or the shock arrival rate can improve the system performance while lowering the long-run average cost rate.
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