Support equipment dynamic prognostic model based on operation mission

Support equipment is indispensable in the maintenance support process. Its allocation including what kind of support equipment and how many for each of them to be equipped determines whether relevant maintenance support tasks can be started and finished timely and effectively at maintenance support stations, and has a huge influence on the support system´s cost, footprint and versatility. So far, in the materiel in-service phase, the allocation quantity of support equipment mainly depend on traditional experience is different from the actual requirement, which often lead to the amount of some kind of support equipment too much or too little. How to combine components reliability level and data of materiel operation mission, upon completion of the specified support task requirements, improving the timeliness, deployment and economy level of support system, prognosing and optimizing the allocation quantity of support equipment, are current outstanding issues. This article, based on the dynamic materiel operation mission, utilizes the exponential smoothing method, combines the components reliability level, and analyzes the materiel operation mission and maintenance support activities, to obtain the materiel operation mission frequency and support activities frequency. Then, based on the operate characteristics of support equipment in these activities, the quantity of support equipment can be calculated preliminarily. Further, according to the efficiency requirements of support equipment in the materiel in-service phase, this paper modifies and optimizes the initial support equipment quantity by queuing theory, and builds support equipment dynamical prognostic model based on operation mission. Finally, the paper present an actual application case to verify the model, meanwhile, provides the method and paradigm for the support department to determine the optimal support equipment configuration quantity in the materiel in-service phase, which have important theoretical - ignificance and engineering application value.