Robust design approach to the minimization of functional performance variations of products and systems

J. ZHANG, H. DU, D. XUE, P. GU

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PDF(847 KB)
Front. Mech. Eng. ›› 2021, Vol. 16 ›› Issue (2) : 379-392. DOI: 10.1007/s11465-020-0607-1
RESEARCH ARTICLE
RESEARCH ARTICLE

Robust design approach to the minimization of functional performance variations of products and systems

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Abstract

Functional performance variations of products and systems are often used to measure the qualities of products and systems considering the changes in the design parameter values caused by uncertainties. A robust design approach has been developed in this research to minimize the functional performance variations considering the design parameter uncertainties by identifying the boundaries of the functional performance variations through optimization. In this work, a mathematical model is developed to describe the relationships among functional performance, design configurations and parameters, and design parameter uncertainties. A multi-level optimization model is established to identify: (1) The optimal design configuration, (2) the optimal values of design parameters, and (3) the boundaries of functional performance variations. Sensitivity analysis considering the impact of parameter uncertainties on functional performance variation boundaries has also been conducted. A case study on the design of a truss system has been conducted. Case study results show that the sensitivities of functional performance variation boundaries to the design parameter uncertainties can be reduced significantly using the new robust design approach.

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Keywords

product design / robust design / design optimization / uncertainties

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J. ZHANG, H. DU, D. XUE, P. GU. Robust design approach to the minimization of functional performance variations of products and systems. Front. Mech. Eng., 2021, 16(2): 379‒392 https://doi.org/10.1007/s11465-020-0607-1

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Acknowledgements

The authors wish to thank the National Key R&D Program of China (Grant No. 2018YFB1701701), the National Natural Science Foundation of China (Grant No. 51505269), and the Sailing Talent Program of Guangdong Province, China for providing financial support for this research.

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2021 Higher Education Press
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