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Data-driven multi-objective affective product design integrating three-dimensional form and color

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Abstract

Three-dimensional (3D) form and color are the main appearance elements that arouse product emotion. To use more complete data of appearance and emotion and their comprehensive coupling relationship to improve the emotional design quality, this paper proposes a novel method of data-driven multi-objective affective product design integrating 3D form and color. Based on neural network and machine learning algorithms, it constructs multiple models covering the entire process of affective product design. The models include a mathematical model for quantifying 3D form’s complete surface and color to obtain their complete mixed data, a recognition model for identifying more accurate and comprehensive emotions and obtaining complete emotional data by using the mixed data to participate in the recognition modeling, a prediction model for establishing a comprehensive coupling relationship between appearance and emotion and achieving more accurate emotion prediction, and an optimization model for better realizing optimal designs in response to multiple emotions by utilizing the comprehensive coupling relationship. To validate the effectiveness and practicability of the proposed method, its design application system and an experimental study on two design models (Model I and Model II) are constructed and applied in car design. Model I uses the more complete mixed data for design, while Model II does not. The results show that the emotional design quality and efficiency of Model I are better than those of Model II, which highlights the value of complete data and comprehensive coupling relationship for affective product design.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (Grant No. 71661023) and Jiangxi Province Culture and Art Science Planning Project (Grant No. YG2020119).

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Authors and Affiliations

  1. Advanced Manufacturing School, Nanchang University, Nanchang, 330031, China

    Zeng Wang & Weidong Liu

  2. Architecture and Design College, Nanchang University, Nanchang, 330031, China

    Zeng Wang & Minglang Yang

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  1. Zeng Wang
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  2. Weidong Liu
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  3. Minglang Yang
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Contributions

ZW contributed to the conceptualization, investigation, experiment, writing of the original draft, writing of the review, and editing. MY contributed to the review and analysis with constructive discussions. WL contributed to the review and analysis with constructive discussions, and funding acquisition.

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Correspondence to Weidong Liu.

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Wang, Z., Liu, W. & Yang, M. Data-driven multi-objective affective product design integrating three-dimensional form and color. Neural Comput & Applic 34, 15835–15861 (2022). https://doi.org/10.1007/s00521-022-07232-2

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