Model for Estimating Spare Parts Requirements for Future Missions

Bachman, Tovey C.; Kline, Robert C.

doi:10.2514/6.2004-5978

Cited by 8 publications

(11 citation statements)

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“…and is sometimes referred to as "outstanding orders" [1], or as the "number in the pipeline" [3]. Note that the interval t o t f is the duration the component has operated for.…”

Section: A Dedicated Spare Partsmentioning

confidence: 99%

“…Shishko [2] has modeled costs of spares and repairs in estimating operations costs for the International Space Station. Bachman and Kline [3] have developed a model for estimating spare parts requirements for space exploration missions.…”

Section: Nomenclaturementioning

confidence: 99%

“…The expected backorder level, B j , is the expected value of the difference between the actual number of spares that are available and the required number of spares (as driven by the number of failed components). It is therefore computed as [3] B j…”

Section: A Dedicated Spare Partsmentioning

confidence: 99%

“…The model presented in [3] is used in this work as a base case (which is referred to as the "dedicated case" in this study) in which components are assumed to be used for only particular elements. An enhanced model is then formulated in which the parts can be assumed to be reconfigurable (or common) and thus an interchange of parts between mission elements subject to their operational state is permitted.…”

Section: Nomenclaturementioning

confidence: 99%

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Spare Parts Requirements for Space Missions with Reconfigurability and Commonality

Siddiqi

Weck

2007

Journal of Spacecraft and Rockets

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The logistics resources (in the form of spare parts) for future exploration missions to the moon and Mars can have significant mass and volume requirements. In this study it is shown that reconfigurable or common parts that allow use of the same component in different mission elements, can be a means of reducing the required number of spares. A model for determining the system availability as a function of spares level is developed for a mission that utilizes elements with reconfigurable or common parts. An explicit consideration of the operating scenario is made that allows the use of components from elements that are not operating at a given time. A Mars surface exploration mission is used to illustrate the application of this model. It is shown, for the specific example studied in the analysis, that the same level of system availability can be achieved with 33-50% fewer spares if the parts are reconfigurable or common across different mission elements. NomenclatureAt i = availability at t i Bt i = expected backorder level at t i B c s; t i = expected backorder level at t i for spares level s E = number of total elements in the mission l = failure rate (failures per day) N = total number of units among all elements and including spares repository Ps = probability of having s spares available pn = probability of n failures q e = no. of units of a component in element e s = total number of spares s E = maximum number of spares available from idle elements s I = initial number of spares in repository t i = time instances at which operating elements change their state e t k = binary variable with value 1 if element e is operating in interval t k t i = percentage of elements operating at t i = mean number of failures

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“…and is sometimes referred to as "outstanding orders" [1], or as the "number in the pipeline" [3]. Note that the interval t o t f is the duration the component has operated for.…”

Section: A Dedicated Spare Partsmentioning

confidence: 99%

Section: Nomenclaturementioning

confidence: 99%

Section: A Dedicated Spare Partsmentioning

confidence: 99%

Section: Nomenclaturementioning

confidence: 99%

See 2 more Smart Citations

Spare Parts Requirements for Space Missions with Reconfigurability and Commonality

Siddiqi

Weck

2007

Journal of Spacecraft and Rockets

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“…A shortage in spare parts for infrastructure reduces mission performance either because it requires the crew to cancel planned exploration activity to perform repairs (rather than replacements), or in an extreme case to abandon the mission. Bachman and Kline [54] developed a hybrid parametric-analytical model for estimating the required spare parts requirements for exploration of the Moon, Mars, and beyond. In this model, as showin in Figure 4-1, demand (failures) occur according to a Poisson distribution with arrival rate.…”

Section: Infrastructure Availabilitymentioning

confidence: 99%

Cargo Revenue Management for Space Logistics

Armar

Weck

2009

AIAA SPACE 2009 Conference &Amp; Exposition

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This thesis covers the development of a framework for the application of revenue management, specifically capacity control, to space logistics for use in the optimization of mission cargo allocations, which in turn affect duration, infrastructure availability, and forward logistics. Two capacity control algorithms were developed; the first is based on partitioning of Monte Carlo samples while the second is based on bid-pricing with high-frequency price adjustments. The algorithms were implemented in Java as a plugin module to SpaceNet 2.0, an existing integrated modeling and simulation tool for space logistics. The module was tested on a lunar exploration concept which emphasizes global exploration of the Moon using mobile infrastructure. Results suggest that revenue management produces better capacity allocations in shorter duration missions, while producing nominal capacity allocations (i.e. those in the deterministic case) in the long run.

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