Abstract
The standby sparing technique is widely applied in diverse industries to reduce system downtime. This paper models a new class of standby sparing systems operating in a random environment, modeled by two independent shock processes from different sources affecting distinct sets of components during the mission. The operating and standby components may be replaced or refilled based on their status and the number of shocks experienced, which are observable through periodic inspections. The shock-based inspection and component replacement/addition policy (SBP) is defined in a parametric form, and an optimization problem is formulated to find the SBP that minimizes the expected cost of task accomplishment (ECTA). The objective function of the formulated optimization problem is evaluated using a fast numerical procedure based on system state transitions. The optimal SBP is determined using brute force enumeration over the possible values of integer policy parameters. A detailed case study using a sensor system is performed to examine the effects of key cost and shock parameters on the ECTA and optimization results, offering managerial insights. A comparison between the proposed SBP and an existing time-based policy demonstrates the advantage of the proposed policy in reducing overall ECTA.