An Evolutionary Design Method of Product Form Inspired by Spider-webs

Zhang, Shu; Shi, Liu; Su, Jian Ning; Zhou, Aimin; Wang, Shi

doi:10.14733/cadaps.2022.1-25

Cited by 3 publications

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An Improved Cobweb Grey Target Decision-Making Model for Multiple Kansei Images Based on Variable Weight Theory

Zhang

Wang

et al. 2023

Preprint

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The use of constant weights reduces the accuracy of cognitive evaluation results, and the current design decision-making methods ignore the relationships between Kansei images. To solve these problems, an improved cobweb grey target decision-making method for multiple Kansei images based on variable weight theory is proposed. We take a hand-held electric drill as an example for exploration. First, according to the initial weight relationships of Kansei images, variable weight theory is used to identify the Kansei image variable weights of samples, and the variable weight comprehensive evaluation results for each sample are obtained. Then, based on the correlation and angle of the Kansei images, a cobweb diagram is drawn to represent the Kansei image relationship of each sample. Combined with the cobweb grey target decision-making model for multiple Kansei images, an improved cobweb grey target decision-making method for multiple Kansei images is constructed. The decision coefficients of 10 samples are obtained as 0.0567, 0, 0.0205, 0.0478, 0.0155, 0.0272, 0.0292, 0.0402, 0.0155 and 0.0470. Through the comparison and ranking of the decision coefficients, sample 2 is determined to be the relatively optimal design reference sample. Finally, the constructed model is compared with the cobweb grey target decision-making model for multiple Kansei images and the technique for order preference by similarity to ideal solution (TOPSIS). The difference coefficients of the three methods are obtained, namely, 0.5627, 0.4957 and 0.3613. The results show that the difference coefficient of the proposed method is the largest, and it can reflect the decision-making thinking of designers and improve the discrimination among the decision-making results to a certain extent.

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An Improved Cobweb Grey Target Decision-Making Model for Multiple Kansei Images Based on Variable Weight Theory

Zhang

Wang

et al. 2023

Preprint

Self Cite

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Fuzzy Relationship between Kansei Images: A Grey Decision-Making Method for Product Form

Wang,

Zhang,

et al. 2024

Applied Sciences

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Current design decision-making methods ignore the fuzzy relationship between Kansei images, and the use of constant weights reduces the accuracy of cognitive evaluation results. To solve these problems, this paper proposes a grey decision-making method for product form driven by the fuzzy relationship between Kansei images. First, according to the initial weight of the Kansei images, variable weight theory is used to determine the Kansei image variable weights of the samples, and the variable weight comprehensive evaluation results for each sample are obtained. Then, based on the correlation and angle of the Kansei images, a cobweb diagram is drawn to represent the fuzzy relationship between the Kansei images of each sample. Combined with the cobweb grey target decision-making model (CGTDM) for multiple Kansei images, decision coefficients are calculated. The decision coefficients are compared and ranked to determine the relatively optimal design reference sample. Finally, the constructed model is compared with the CGTDM for multiple Kansei images and TOPSIS. The results show that the difference coefficient of the proposed method is the largest, and it can reflect the decision-making thinking of the designers and improve the discrimination among the decision-making results to a certain extent.

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A Brief Review of Computational Product Design: A Brand Identity Approach

2023

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On the way to designing customized products as one of the core activities of Industry 4.0, the strategy of computational design emerges as a unique design process due to its flexibility and simplicity. More specifically, the aforementioned strategy is concerned with the study of brand identity and its description in the development of commercial industrial products. The proposed design approach is focused on the study of branded product forms following computational design methodologies, i.e., employing textual or/and visual programming languages. The paper presents an overview of in-depth research studies which deal with the systematic way of creation, evolution, and transformation of industrial products with modern digital tools. Through the review, 100 studies have been analyzed over the last 15 years. The background of this research includes definitions from the specific four pillars of the modern theory of industrial design, e.g., product design, digital design, visual representation, and product identity. Furthermore, the current paper combines the use of computational design with specific parameters of visual brand elements in order to develop a methodological tool for the mass customization of industrial products. Moreover, the proposed framework offers a great deal of flexibility in both design and manufacturing, while many design alternatives could become available in a very short time. Finally, the impact of this paper is the correlation between computational design techniques and the theoretical background of brand identity principles (i.e., shapes, geometries, styles, textures, colors, and materials) for inspiring novel ideas among engineers, designers, and marketers.

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An Evolutionary Design Method of Product Form Inspired by Spider-webs

Cited by 3 publications

References 0 publications

An Improved Cobweb Grey Target Decision-Making Model for Multiple Kansei Images Based on Variable Weight Theory

An Improved Cobweb Grey Target Decision-Making Model for Multiple Kansei Images Based on Variable Weight Theory

Fuzzy Relationship between Kansei Images: A Grey Decision-Making Method for Product Form

A Brief Review of Computational Product Design: A Brand Identity Approach

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