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Development of a Mathematica Tool for Implementation of a Prognostics Decision-Making Process Based on Component Life History
ARMY MATERIEL SYSTEMS ANALYSIS ACTIVITY ABERDEEN PROVING GROUND MD
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The key benefit of prognostics is that it can be used to reduce failure risks during deployments and missions when failure is particularly disadvantageous and maintenance inconvenient due to the reduced logistics footprint. One approach to prognostics is to monitor usage in conjunction with an aging model thereby keeping track of remaining component lifetime. This enables one to track usage with on-board sensors and embed an algorithm in on-system logistics software that will automatically generate maintenance alerts and recommendations so that a covered component can likely be replaced before failure as its remaining lifetime decreases and failure risk increases. An additional benefit of usage-based prognostics is that it can also be used to identify an optimum replacement age that minimizes life cycle costs for components that age, provided the costs of in-service failure are greater than planned replacement which is often the case. This report documents the development and application of a collection of functions written in Mathematica that can be used to implement usage-based prognostics using life distributions for components that become less reliable with usage.
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