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Exploring the Dual Potential of Artificial Intelligence-Generated Content in the Esthetic Reproduction and Sustainable Innovative Design of Ming-Style Furniture

Author

Listed:
  • Yali Wang

    (School of Mechanical Science & Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Yuchen Xi

    (School of Mechanical Science & Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Xinxiong Liu

    (School of Mechanical Science & Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Yan Gan

    (School of Mechanical Science & Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

Abstract

The present research aims to explore the dual potential of artificial intelligence-generated content (AIGC) technology in the esthetic reproduction of Ming-style furniture and its innovative design while promoting sustainable practices and cultural heritage preservation. For this purpose, a combination of methodologies integrating the principles of grounded theory, empirical research, sustainable design, and design practice and evaluation techniques is employed. The results are as follows: First, the three-level coding method in grounded theory is used to construct a multi-dimensional esthetic feature library of Ming-style furniture, including 6 esthetic feature dimensions and 102 groups of esthetic elements. Second, a set of databases specifically for Ming-style furniture is developed based on the Midjourney platform. The AIGC exclusive toolkit for furniture (MFMP) contains a language package of 61 keywords and a basic formula for Ming-style furniture design. The MFMP toolkit accurately reproduces Ming-style furniture esthetics through empirical validation. Finally, combined with sustainable design principles, a new path is explored in order to utilize the MFMP toolkit for the sustainable and innovative design of new Chinese-style furniture. The research results demonstrate that AIGC enhances traditional and modern furniture design, offering tools for industry growth in a sustainable way and preserving cultural heritage.

Suggested Citation

  • Yali Wang & Yuchen Xi & Xinxiong Liu & Yan Gan, 2024. "Exploring the Dual Potential of Artificial Intelligence-Generated Content in the Esthetic Reproduction and Sustainable Innovative Design of Ming-Style Furniture," Sustainability, MDPI, vol. 16(12), pages 1-24, June.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:12:p:5173-:d:1417020
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    References listed on IDEAS

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    1. Andrea Sujova & Katarina Marcinekova & Stefan Hittmar, 2017. "Sustainable Optimization of Manufacturing Process Effectiveness in Furniture Production," Sustainability, MDPI, vol. 9(6), pages 1-15, June.
    2. Timur Narbaev & Diana Amirbekova, 2021. "Research Productivity in Emerging Economies: Empirical Evidence from Kazakhstan," Publications, MDPI, vol. 9(4), pages 1-19, November.
    3. Maja Hosta & Vesna Zabkar, 2021. "Antecedents of Environmentally and Socially Responsible Sustainable Consumer Behavior," Journal of Business Ethics, Springer, vol. 171(2), pages 273-293, June.
    4. Rosa Dangelico & Devashish Pujari, 2010. "Mainstreaming Green Product Innovation: Why and How Companies Integrate Environmental Sustainability," Journal of Business Ethics, Springer, vol. 95(3), pages 471-486, September.
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    Cited by:

    1. Yi Huang & Xiang Li & Feng Gan & Tianwei Gu, 2024. "Research on Sustainable Intelligent Drying Wardrobe Design Strategy Based on Importance–Performance Analysis," Sustainability, MDPI, vol. 16(23), pages 1-18, December.
    2. Shimin Pan & Rusmadiah Bin Anwar & Nor Nazida Binti Awang & Yinuo He, 2025. "Constructing a Sustainable Evaluation Framework for AIGC Technology in Yixing Zisha Pottery: Balancing Heritage Preservation and Innovation," Sustainability, MDPI, vol. 17(3), pages 1-29, January.

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