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Achieving eco-innovative smart glass design with the integration of opinion mining, QFD and TRIZ.
Lee, C K M; Tsang, Y P; Chong, W W; Au, Y S; Liang, J Y.
Afiliación
  • Lee CKM; The Hong Kong Polytechnic University, Kowloon, Hong Kong. ckm.lee@polyu.edu.hk.
  • Tsang YP; Laboratory for Artificial Intelligence in Design, New Territories, Hong Kong. ckm.lee@polyu.edu.hk.
  • Chong WW; The Hong Kong Polytechnic University, Kowloon, Hong Kong.
  • Au YS; Laboratory for Artificial Intelligence in Design, New Territories, Hong Kong.
  • Liang JY; Laboratory for Artificial Intelligence in Design, New Territories, Hong Kong.
Sci Rep ; 14(1): 9822, 2024 Apr 29.
Article en En | MEDLINE | ID: mdl-38684754
ABSTRACT
Modern consumption patterns lead to massive waste, which poses challenges in storage and highlights the urgent need for more sustainable product development. Customer feedback on products plays a crucial role in product design, yet previous studies overlooked these invaluable insights. In response, this study introduces a novel systematic methodology that integrates the strengths of text mining, Quality Function Deployment (QFD), and the Theory of Inventive Problem Solving (TRIZ). Text mining techniques are utilized to extract customer requirements from online platforms, while QFD is used to translate these requirements into technical specifications. By integrating the contradiction matrix from TRIZ theory with the triptych, technical conflicts are resolved. The design process for next-generation smart glasses is employed as an illustrative case to validate the proposed integrated innovation design approach. Analytical outcomes suggest that the introduced methodology can effectively address sustainable product design challenges and sets the stage for future advancements in smart glasses.
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Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article