Spare parts stock control for redundant systems using reliability centered maintenance data

In the classical approach to determine how many spare parts to stock, the spare parts shortage costs or the minimum fill rate is a key factor. A difficulty with this approach lies in the estimation of these shortage costs or the determination of appropriate minimum fill rates. In an attempt to overcome this problem, we propose to use the data gathered in reliability centered maintenance (RCM) studies to determine shortage costs. We discuss the benefits of this approach. At the same time, the approach gives rise to complications, as the RCM study determines downtime costs of the underlying equipment, which have a complex relation with the shortage cost for spare parts in case multiple pieces of equipment have different downtime costs. A further complication is redundancy in the equipment. We develop a framework that enables the modeling of these more complicated systems. Based on the framework, we propose an approximative, analytic method that can be used to determine minimum stock quantities in case of redundancy and multiple systems. In a quantitative study we show that the method performs well. Moreover, we show that including redundancy information in the stocking decision gives significant cost benefits.

► We argue that RCM data is valuable for spare parts inventory control.
► We model spare part inventory control for redundant systems.
► Methods are developed to approximate the downtime costs in the model.
► The approximate methods are accurate and fast.
► Redundancy information improves spare parts inventory control significantly.