Research on multi-channel interaction optimization design of household intelligent clothes hanger based on Kano-QFD

XiYu Gu; HuaMing Peng

doi:10.1117/12.2667199

22 February 2023 Research on multi-channel interaction optimization design of household intelligent clothes hanger based on Kano-QFD

XiYu Gu, HuaMing Peng

Author Affiliations +

Proceedings Volume 12587, Third International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022); 1258702 (2023) https://doi.org/10.1117/12.2667199
Event: Third International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022), 2022, Shanghai, China

Abstract

To optimize the multi-channel interactive experience of the household intelligent clothes hangers, the Kano model is used to qualitatively analyze 15 elements from the two demand levels of "practicality and ease of use", and the SII-DDI matrix analysis diagram is made. The importance ranking of 18 design requirements in two dimensions of "function and interaction" is constructed by the QFD method. The results show that: (1) "convenient storage" and "knowing process" are the requirements of household intelligent clothes hanger users "Remote control", "aseptic", "quick drying" and "ensuring night safety" are expected requirements. (2) The absolute importance of "client remote control", "human sense recognition" and "visual display operation" are 447, 428 and 428 respectively, which are three interaction modes with high user satisfaction. (3) The design points of "folding storage" and "intelligently matching the drying temperature to ensure the comfort of special fabrics" are the most important for the product function upgrading of the existing household intelligent clothes hanger Market.

Citation Download Citation

XiYu Gu and HuaMing Peng "Research on multi-channel interaction optimization design of household intelligent clothes hanger based on Kano-QFD", Proc. SPIE 12587, Third International Seminar on Artificial Intelligence, Networking, and Information Technology (AINIT 2022), 1258702 (22 February 2023); https://doi.org/10.1117/12.2667199

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