Inventory optimization of spare parts for k-out-of-n pairs: G balanced systems

Existing research on the inventory policy rarely addresses the multi-base, multi-item spare part problem for k -out-of- n pairs: G balanced systems. To fill this gap, this paper explores a novel inventory policy for repairable items on balanced systems. A replacement action at a base or a repair action at the depot will be decided once a component fails. Considering the failure characteristic of balanced systems, the corresponding unit on the symmetric position immediately stops working and is regarded as a standby unit if a unit fails. A rearrangement action can be performed once there are more than two standby units in the balanced system. A Markov model is formulated to minimize the system’s failure probability under the constraint of costs by optimizing the order policy. An optimal balance between the system failure probability and the inventory cost is explored by a Markov prediction method. Our findings indicate that the proposed joint optimization model is effective in managing the inventory problem for repairable items within k -out-of- n : G systems in the industrial field. The managerial implication of inventory policy is also further highlighted by conducting sensitivity analyses under different conditions, providing valuable insights for practitioners.