Uncertainty quantification metrics for whole product life cycle cost estimates in aerospace innovation

Simple item page
dc.contributor.authorSchwabe, Oliver
dc.contributor.authorShehab, Essam
dc.contributor.authorErkoyuncu, John Ahmet
dc.date.accessioned2019-12-16T11:35:27Z
dc.date.available2019-12-16T11:35:27Z
dc.date.issued2015-06-25
dc.description.abstractThe lack of defensible methods for quantifying cost estimate uncertainty over the whole product life cycle of aerospace innovations such as propulsion systems or airframes poses a significant challenge to the creation of accurate and defensible cost estimates. Based on the axiomatic definition of uncertainty as the actual prediction error of the cost estimate, this paper provides a comprehensive overview of metrics used for the uncertainty quantification of cost estimates based on a literature review, an evaluation of publicly funded projects such as part of the CORDIS or Horizon 2020 programs, and an analysis of established approaches used by organizations such NASA, the U.S. Department of Defence, the ESA, and various commercial companies. The metrics are categorized based on their foundational character (foundations), their use in practice (state-of-practice), their availability for practice (state-of-art) and those suggested for future exploration (state-of-future). Insights gained were that a variety of uncertainty quantification metrics exist whose suitability depends on the volatility of available relevant information, as defined by technical and cost readiness level, and the number of whole product life cycle phases the estimate is intended to be valid for. Information volatility and number of whole product life cycle phases can hereby be considered as defining multi-dimensional probability fields admitting various uncertainty quantification metric families with identifiable thresholds for transitioning between them. The key research gaps identified were the lacking guidance grounded in theory for the selection of uncertainty quantification metrics and lacking practical alternatives to metrics based on the Central Limit Theorem. An innovative uncertainty quantification framework consisting of; a set-theory based typology, a data library, a classification system, and a corresponding input-output model are put forward to address this research gap as the basis for future work in this field.en_UK
dc.identifier.citationSchwabe O, Shehab E, Erkoyuncu J. (2015) Uncertainty quantification metrics for whole product life cycle cost estimates in aerospace innovation. Progress in Aerospace Sciences, Volume 77, August 2015, pp. 1-24en_UK
dc.identifier.issn0376-0421
dc.identifier.urihttps://doi.org/10.1016/j.paerosci.2015.06.002
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/14838
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectCost estimationen_UK
dc.subjectCost readinessen_UK
dc.subjectInnovationen_UK
dc.subjectUncertainty quantificationen_UK
dc.subjectWhole product life cycleen_UK
dc.titleUncertainty quantification metrics for whole product life cycle cost estimates in aerospace innovationen_UK
dc.typeArticleen_UK

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Uncertainty_quantification_metrics_for_whole_product_life_cycle-2015.pdf
Size:
480.01 KB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.63 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Staff publications (SATM)