Optimal spares analysis for a networking system manufacturer

Once the design of a complex system has been finalized and the reliability of key components has been determined, it is important to develop a sparing process to achieve maximum system availability. Ideally, increasing the number of spare components increases system availability, but due to cost considerations, this is not the means to obtain a feasible solution. The question of how to optimize the number of spare components is further complicated when the repair cycle of failed components is taken into account. A networking systems manufacturer sought to optimize their spares in order to meet customer contracts. Many of their contracts require them to send a replacement within a specified period of time from when a failure is reported, and the contracts also specify that the failed device should be sent back for repair. To meet this requirement, the manufacturer set up spares depots in centralized locations from which the replacements are shipped. Upon receipt of a replacement unit from the spares depot, failed units are returned to the repair facility for repair. Once the repairs have been completed, the repaired units are returned to the spares depot and used for future shipments. Using device MTBF, purchased quantities at the depot location, and repair cycle time, a spares optimization was performed to minimize cost. A process was also developed to analyze the effects that a proposed customer contract would have on the existing depot spares quantities. In this paper, we show how this process was modeled using a software analysis tool that supports Reliability Block Diagram (RBD) analysis with spares optimization. The easily configured model is capable of performing spares optimizations for multiple depot locations, adjusting for changes to customer contracts, and analyzing the effects that proposals induce on the optimized quantity. The model illustrated can be easily adjusted and applied to any situation where customer spare analysis is required.