Research Papers: Design for Manufacture and the Life Cycle

Sensitivity Analysis in Quantified Interval Constraint Satisfaction Problems

[+] Author and Article Information
Jie Hu, Aiguo Cheng, Zhihua Zhong

The State Key Laboratory of Advanced Design
and Manufacturing for Vehicle Body,
Hunan University,
Changsha, Hunan 410082, China

Yan Wang

Multiscale Systems Engineering Research Group,
School of Mechanical Engineering,
Georgia Institute of Technology,
Atlanta, GA 30332

Contributed by the Design for Manufacturing Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received October 9, 2013; final manuscript received December 17, 2014; published online February 6, 2015. Assoc. Editor: Rikard Söderberg.

J. Mech. Des 137(4), 041701 (Apr 01, 2015) (11 pages) Paper No: MD-13-1458; doi: 10.1115/1.4029513 History: Received October 09, 2013; Revised December 17, 2014; Online February 06, 2015

Interval is an alternative to probability distribution in quantifying uncertainty for sensitivity analysis (SA) when there is a lack of data to fit a distribution with good confidence. It only requires the information of lower and upper bounds. Analytical relations among design parameters, design variables, and target performances under uncertainty can be modeled as interval-valued constraints. By incorporating logic quantifiers, quantified constraint satisfaction problems (QCSPs) can integrate semantics and engineering intent in mathematical relations for engineering design. In this paper, a global sensitivity analysis (GSA) method is developed for feasible design space searching problems that are formulated as QCSPs, where the effects of value variations and quantifier changes for design parameters on target performances are analyzed based on several proposed metrics, including the indeterminacy of target performances, information gain of parameter variations, and infeasibility of constraints. Three examples are used to demonstrate the proposed approach.

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Topics: Design
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Grahic Jump Location
Fig. 1

The relations among the concepts developed in the proposed method

Grahic Jump Location
Fig. 2

Sensitivity zones of X1X3 with respect to Y

Grahic Jump Location
Fig. 3

Result comparison between the (a) proposed method and (b) traditional local SA method

Grahic Jump Location
Fig. 4

Sensitivity zones of design parameters in scenario 1 (all universal) and scenario 2 (Nf existential)



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