In this work, we propose an integrated framework for optimization under uncertainty that can bring both the design objective robustness and the probabilistic design constraints into account. The fundamental development of this work is the employment of an inverse reliability strategy that uses percentile performance for assessing both the objective robustness and probabilistic constraints. The percentile formulation for objective robustness provides us an accurate evaluation of the variation of an objective performance and a probabilistic measurement of the robustness. We can obtain more reasonable compound noise combinations for a robust design objective compared to using the traditional approach proposed by Taguchi. The proposed formulation is very efficient to solve since it only needs to evaluate the constraint functions at the required reliability levels. The other major development of this work is a new search algorithm for the Most Probable Point of Inverse Reliability (MPPIR) that can be used to efficiently evaluate percentile performances for both robustness and reliability assessments. Multiple strategies are employed in the MPPIR search, including using the steepest ascent direction and an arc search. The algorithm is applicable to general non-concave and non-convex performance functions of random variables following any continuous distributions. The effectiveness of the MPPIR search algorithm is verified using example problems. Overall, an engineering example on integrated robust and reliability design of a vehicle combustion engine piston is used to illustrate the benefits of our proposed method.
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July 2004
Technical Papers
An Integrated Framework for Optimization Under Uncertainty Using Inverse Reliability Strategy
Xiaoping Du,
Xiaoping Du
Department of Mechanical and Aerospace Engineering, University of Missouri–Rolla, Rolla, MO 65409
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Agus Sudjianto,
Agus Sudjianto
Ford Motor Company, Dearborn, MI 48121-4091
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Wei Chen
Wei Chen
Department of Mechanical Engineering, Northwestern University, Evanston, IL 60208-3111
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Xiaoping Du
Department of Mechanical and Aerospace Engineering, University of Missouri–Rolla, Rolla, MO 65409
Agus Sudjianto
Ford Motor Company, Dearborn, MI 48121-4091
Wei Chen
Department of Mechanical Engineering, Northwestern University, Evanston, IL 60208-3111
Contributed by the Design Automation Committee for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received January 2003; revised January 2004. Associate Editor: G. M. Fadel.
J. Mech. Des. Jul 2004, 126(4): 562-570 (9 pages)
Published Online: August 12, 2004
Article history
Received:
January 1, 2003
Revised:
January 1, 2004
Online:
August 12, 2004
Citation
Du, X., Sudjianto, A., and Chen, W. (August 12, 2004). "An Integrated Framework for Optimization Under Uncertainty Using Inverse Reliability Strategy ." ASME. J. Mech. Des. July 2004; 126(4): 562–570. https://doi.org/10.1115/1.1759358
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