Spares Provisioning Model (SPM)
The spares provisioning model computes stock levels for spare parts, both reparable and consumable, at as many as four levels of supply support ranging from base to depot. Users of SPM may choose either the optimization algorithm employing a Lagrange multiplier with one of three measures of effectiveness (fill rate, backorders and operational rate) or instead choose a simplified computational technique (cost category) that closely approximates the results of optimization. For more detail on SPM click here: SPM Model.
Reliability and Mission Availability (RAMA)
RAMA is a simulation model that estimates end item readiness in terms of such measures of effectiveness (MOEs) as sortie generation rate, operational availability and dispatch reliability. The model addresses the end item's specific scenario and maintenance operations as well as the reliability, maintainability and logistics resource levels at the module level. For more detail on RAMA click here: RAMA Model.
Supportability Figure of Merit (SFOM) Model
The SFOM model assesses the inherent supportability of systems by evaluating several important measures of effectiveness (MOEs) as a function of the system's design characteristics. An overall figure of merit is computed given specific weighting factors for each MOE. For more detail on SFOM click here: SFOM Model.
Operational Availability (Ao)
The Ao model calculates the operational availability (defined as the ratio of ready time to calendar time) for a system based on its reliability and maintainability design characteristics and the level of logistics resources. This model contains separate formulas that distinguish between systems operated continuously (e.g., a radar station) and those operated intermittently (e.g., aircraft). For more detail on Ao click here: Ao Model.
Measures of effectiveness relevant to surge operations include sortie generation rate (SGR), combat rate (CR) and sortie loss rate (SLR). These MOEs all make use of the parameter Break Rate, defined as the probability that an end item incurs a failure that must be fixed before the system can be used again. For more information on surge MOEs and break rate and how they are used in S models click here: Surge MOEs.
Repair Level Analysis (RLA) Model
The RLA model determines which maintenance policy (repair at depot, repair at base, discard item) yields the lowest life cycle cost. The RLA process also addresses non-economic factors impacting maintenance policy. A simple repair/discard graphic screening technique is shown for use early in the design of an equipment. When several equipments share the same support equipment or other logistics asset, it may not be appropriate to prorate the cost of the asset among the equipments. The genetic algorithm is shown to provide a way to determine maintenance policy while avoiding the pitfalls of prorating. Employing such concepts as chromosomes, genes, mutation and population, GA provides an efficient search strategy. For more detail on RLA click here: RLA Model.
Reliability Investment Optimization (RIO) Model
The RIO model determines the optimal level of investment in reliability improvement that minimizes the life cycle cost of a system or module. For more detail on RIO click here: RIO Model.
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