Research Papers

Understanding the Impact of Subjective Uncertainty on Architecture and Supplier Identification in Early Complex Systems Design

[+] Author and Article Information
Yun Ye

Laboratoire Génie Industriel, Ecole Centrale Paris, Grande Voie des Vignes, 92 295 Châtenay-Malabry Cedex, France e-mail: inesye@gmail.com

Marija Jankovic

Laboratoire Génie Industriel, Ecole Centrale Paris, Grande Voie des Vignes, 92 295 Châtenay-Malabry Cedex, France e-mail: marija.jankovic@ecp.fr

Gül E. Kremer

Engineering Design and Industrial Engineering, The Pennsylvania State University, 213T Hammond Building, University Park, PA 16802 e-mail: gkremer@psu.edu

1Corresponding author.

Manuscript received September 30, 2014; final manuscript received April 2, 2015; published online July 1, 2015. Assoc. Editor: Alba Sofi.

ASME J. Risk Uncertainty Part B 1(3), 031005 (Jul 01, 2015) (11 pages) Paper No: RISK-14-1068; doi: 10.1115/1.4030463 History: Received September 30, 2014; Accepted April 27, 2015; Online July 01, 2015

The 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; type-1 fuzzy sets and 2-tuple 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.

Copyright © 2015 by ASME
Topics: Uncertainty , Design
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Generation of all possible architectures

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Function satisfaction level by modules

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Requirement-function relations

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Requirements satisfaction (without considering expert uncertainty)

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Uncertainty information

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Uncertainty (without considering expert uncertainty)

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Fuzzy numbers for satisfaction levels

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Requirements satisfaction by using type-1 fuzzy sets (values)

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Requirements satisfaction by using type-1 fuzzy sets (membership functions)

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Fuzzy membership function for possibilities

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Uncertainty using type-1 fuzzy sets (values)

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Uncertainty using type-1 fuzzy sets (membership functions)

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Fuzzy results that are partly above the threshold

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Using α-cut to represent the tolerance level

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Requirements satisfaction after defuzzification

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Uncertainty after defuzzification

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Requirements satisfaction using 2-tuple linguistic representation

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Uncertainty using 2-tuple fuzzy linguistic representation

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Fig. 20

Comparison of supplier identification results

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Fig. 21

Changing thresholds without considering subjective uncertainty




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