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Unformatted text preview: as for product improvement such as greater
system reliability, lower cost logistics support, and better
maintenance and spares poli- NASA Systems Engineering Handbook
Systems Analysis and Modeling Issues
Logistics Supportability Models: Two Examples
Logistics supportability models utilize the reliability and maintainability attributes a particular system design, and
other logistics system variables, to quantify the demands (i.e., requirements) for scarce logistics resources during
operations. The models described here were both developed for Space Station Freedom. One is a stochastic
simulation in which each run is a "trial" drawn from a population of outcomes. Multiple runs must be made to
develop accurate estimates of means and variances for the variables of interest. The other is a deterministic
analytic model. Logistic supportability models may be of either type. These two models deal with the unique
logistics environment of Freedom.
SIMSYLS is a comprehensive stochastic simulation of on-orbit maintenance and logistics resupply of
Freedom. It provides estimates of the demand (means and variances) for maintenance resources such as EVA and
IVA, as well as for logistics upmass and downmass resources. In addition to the effects of actual and false ORU
failures, the effects of various other stochastic events such as launch vehicle and ground repair delays can be
quantified. SIMSYLS also produces several measures of operational availability. The model can be used in its
availability mode or in its resource requirements mode.
M-SPARE is an availability-based optimal spares model. It determines the mix of ORU spares at any spares
budget level that maximizes station availability, defined as the probability that no ORU had more demands during
a resupply cycle than it had spares to satisfy those demands. Unlike SIMSYLS, M-SPARE's availability measure
deals only with the effect of spares. M-SPARE starts with a target availability (or budget) and determines the
optimal inventory, a capab...
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