Abstract
In this study we investigate the failure mechanism of the data storage system of a supercomputer and introduce an age-based cost-minimization preventive maintenance (PM) model. The data storage system of a supercomputer consists of hundreds of storage nodes, and each storage node contains several independently and identically distributed nonrepairable hard disks (HDs). Based on the data storage mechanism of the HDs and the failure mechanism of the storage nodes, the k-out-of-n:F system is used to model the data storage nodes. The lifetime of all HDs is assumed to be exponentially distributed. The age-based PM policy is to replace the failed HDs every PM interval or upon system failure. We establish an optimization model to identify the optimal PM interval with the goal of minimizing the long-run average cost while meeting the requirements for system reliability. Our numerical case study shows the application of the present model and method, and analyzes the relationship between the long-run average cost and PM interval.
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