When will spares run-out?

Reliability engineers analyze system and part data after manufacture to determine performance. Reliability analysis is used to make recommendations that permit a system to function longer and dependably. One of the uses of reliability data is in helping to generate probability of failure metrics that aid the logistical analysis team. Mean time between failures (MTBF) of a part is a common reliability metric in support of logistic analysis. A MTBF assumes a constant failure rate of the part performing its required function. Spare analysis is used to predict the number of replacement parts to support the system and uses the MTBF metric for that purpose. Part demand is assumed to be equivalent to the MTBF in logistic analysis. A concern exists with stockage calculations in a mature system that there is possibility of running out of parts. The running out of parts is called a stockout condition. A stockout condition can occur when the demand exceeds the supply of spares or the spare is no longer available. Common policies use d in monitoring the status of spare parts depend on the MTBF equaling the spare part demand. This paper will present a model that differentiates between MTBF and parts demand. Logistics policies based on the enhanced model have a better chance for avoiding either stockout conditions or costs for excessive spare parts.