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A scalable product configuration model and algorithm

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Abstract

The application of product configuration model is an effective way to improve product design and manufacturing efficiency. The traditional product configuration model has a single configuration result, and the configuration model is difficult to be expanded. In order to solve the existing problem, a scalable product configuration model is established based on polychromatic sets theory and corresponding algorithm is proposed. Firstly, product modules are clustered according to function types to establish function block, which is the solving unit of product configuration model. At the same time, multilayer polychromatic set contour-comprising matrices are respectively established from the point of view of needs, product, performance and module. According to actual demand of product configuration, the unified color reasoning algorithm is proposed. And scalable product configuration model and algorithm are proposed based on relative works. Then, the scalability of proposed model is studied from the point of view of needs change and modules change. Finally, the configuration of a special vehicle is introduced to verify the presented model and algorithm, and the results confirmed the effectiveness and rationality of the method.

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Acknowledgements

The project is supported by National Natural Science Foundation of China (Grant No. 51705392) and Xi’an Technological University President Foundation (Grant No. XAGDXJJ16004).

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Authors and Affiliations

  1. School of Mechatronic Engineering, Xi’an Technological University, Xi’an, 710021, Shaanxi, China

    Hu Qiao, Fan Feng & Jianyao Qi

  2. College of Mechanical and Electrical Engineering, Shaanxi University of Science and Technology, Xi’an, 710021, Shaanxi, China

    Ying Xiang

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  1. Hu Qiao
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  2. Fan Feng
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  3. Jianyao Qi
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  4. Ying Xiang
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Correspondence to Ying Xiang.

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Qiao, H., Feng, F., Qi, J. et al. A scalable product configuration model and algorithm. Cluster Comput 22 (Suppl 3), 6405–6415 (2019). https://doi.org/10.1007/s10586-018-2146-7

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  • DOI: https://doi.org/10.1007/s10586-018-2146-7

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