Robust design of configurations and parameters of adaptable products

Jian ZHANG, Yongliang CHEN, Deyi XUE, Peihua GU

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PDF(344 KB)
Front. Mech. Eng. ›› 2014, Vol. 9 ›› Issue (1) : 1-14. DOI: 10.1007/s11465-014-0296-8
RESEARCH ARTICLE

Robust design of configurations and parameters of adaptable products

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Abstract

An adaptable product can satisfy different customer requirements by changing its configuration and parameter values during the operation stage. Design of adaptable products aims at reducing the environment impact through replacement of multiple different products with single adaptable ones. Due to the complex architecture, multiple functional requirements, and changes of product configurations and parameter values in operation, impact of uncertainties to the functional performance measures needs to be considered in design of adaptable products. In this paper, a robust design approach is introduced to identify the optimal design configuration and parameters of an adaptable product whose functional performance measures are the least sensitive to uncertainties. An adaptable product in this paper is modeled by both configurations and parameters. At the configuration level, methods to model different product configuration candidates in design and different product configuration states in operation to satisfy design requirements are introduced. At the parameter level, four types of product/operating parameters and relations among these parameters are discussed. A two-level optimization approach is developed to identify the optimal design configuration and its parameter values of the adaptable product. A case study is implemented to illustrate the effectiveness of the newly developed robust adaptable design method.

Keywords

adaptable product / robust design / optimization / uncertainties

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Jian ZHANG, Yongliang CHEN, Deyi XUE, Peihua GU. Robust design of configurations and parameters of adaptable products. Front. Mech. Eng., 2014, 9(1): 1‒14 https://doi.org/10.1007/s11465-014-0296-8

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Acknowledgements

The authors wish to thank the Leading Talent Project of Guangdong Province, China, the Natural Sciences and Engineering Research Council (NSERC) of Canada, and the National Natural Science Foundation of China (Grant Nos. 51375287 and 51275281) for providing financial supports to this research.

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2014 Higher Education Press and Springer-Verlag Berlin Heidelberg
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