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dc.contributor.authorYe, Yun
dc.contributor.authorJankovic, Marija
dc.contributor.authorKremer, Gأ¼l E.
dc.date.accessioned2017-05-09T01:14:27Z
dc.date.available2017-05-09T01:14:27Z
dc.date.issued2015
dc.identifier.issn2332-9017
dc.identifier.otherRISK_1_3_031005.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl/handle/yetl/156880
dc.description.abstractThe Architecture and Supplier Identification Tool (ASIT) is a design support tool, which enables identification of the most suitable architectures and suppliers in early stages of complex systems design, with consideration of overall requirements satisfaction and uncertainty. During uncertainty estimation, several types of uncertainties that are essential in early design (i.e., uncertainty of modules due to new technology integration, compatibility between modules, and supplier performance uncertainty) have been considered in ASIT. However, it remains unclear whether uncertainty due to expert estimation should be taken into account. From one perspective, expert estimation uncertainty may significantly influence the overall uncertainty, since early complex systems design greatly depends on expert estimation; whereas an opposing perspective argues that expert estimation uncertainty should be neglected given its relatively much smaller scale. In order to understand how expert estimation uncertainty influences the architecture and supplier identification, a comprehensive study of possible modeling approaches has been discussed within the context of ASIT; type1 fuzzy sets and 2tuple fuzzy linguistic representation are selected to integrate subjective uncertainty into ASIT. A powertrain design case is used to compare results between cases considering subjective uncertainty versus cases not considering subjective uncertainty. Finally, implications of considering subjective uncertainty in early conceptual design are discussed.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleUnderstanding the Impact of Subjective Uncertainty on Architecture and Supplier Identification in Early Complex Systems Design
dc.typeJournal Paper
dc.journal.volume1
dc.journal.issue3
dc.journal.titleASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
dc.identifier.doi10.1115/1.4030463
dc.journal.fristpage31005
dc.journal.lastpage31005
dc.treeASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering:;2015:;volume( 001 ):;issue: 003
dc.contenttypeFulltext


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