The effect analysis of multi-echelon inventory models considering demand rate uncertainty and limited maintenance capacity

Abstract

Multi-echelon technique for recoverable item control (METRIC) has been a basic model in spare part stocking problem for high value with relatively low demand items. As METRIC is improved to vari-METRIC, the accuracy of the model is significantly increased. However, METRIC-based analytical models require strict assumptions for calculating spare stock levels. Many researchers have dedicated to relax those assumptions. Most of those efforts become either computing heuristics or relatively complex models. In this study, we propose a relatively simple METRIC-based model for the optimal allocation of spare stocking problems considering uncertain demand rate and limited repair capacity at the same time. Our models can be applicable to minimise either the expected backorders (EBOs) under a certain budget restriction or spending over certain availability. The proposed model relaxes those two assumptions by applying queueing theory and conditional Poisson probability distribution on demand rate. A numerical study shows the precision improvement. The EBO variation of our proposed model is decreased more than 50% when comparing to that of vari-METRIC.