Applied research on the design of protective clothing based on the Kano-QFD-PUGH method

In order to improve the user experience of protective clothing for healthcare workers and reduce the design blindness and subjectivity of developers, we propose a research methodology that combines the Kano model, QFD quality function deployment, and PUGH decision-making scheme to develop conceptual solutions for medical protective clothing design. Firstly, we use the Kano model to identify the user requirements of healthcare workers and construct a hierarchy of functional requirements for protective clothing. Secondly, we use the QFD method to weigh the protective clothing design elements, convert user requirements into design elements, establish a relationship matrix between user requirements and design elements, and generate four conceptual design solutions based on the results. Finally, we use the PUGH decision-making method to filter and select the best concept solution for protective clothing design, and validate the design evaluation. Our results show that the protective clothing solutions designed using the combined Kano-QFD-PUGH system approach have a higher level of satisfaction compared to traditional protective clothing design. This method accurately explores the mapping relationship between user requirements and design functional elements and can be used as a general reliability design method. It helps to improve the development efficiency of designers and the decision-making role for design concept solution preference. Overall, our research methodology provides a comprehensive approach to developing medical protective clothing, which can be useful for designers and decision-makers in the healthcare industry.

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Publication Details

Journal
PLoS ONE
Published
2024-10-24
DOI
https://doi.org/10.1371/journal.pone.0312045
Citations
5
Primary Topic
Color perception and design
Type
article
Field-Weighted Citation Impact
3.22
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article

Applied research on the design of protective clothing based on the Kano-QFD-PUGH method

Shi Li, Hong Li
5 citations
PLoS ONE
Color perception and design
3.22
article

Applied research on the design of protective clothing based on the Kano-QFD-PUGH method

Shi Li, Hong Li
article en
5 citations

Abstract

In order to improve the user experience of protective clothing for healthcare workers and reduce the design blindness and subjectivity of developers, we propose a research methodology that combines the Kano model, QFD quality function deployment, and PUGH decision-making scheme to develop conceptual solutions for medical protective clothing design. Firstly, we use the Kano model to identify the user requirements of healthcare workers and construct a hierarchy of functional requirements for protective clothing. Secondly, we use the QFD method to weigh the protective clothing design elements, convert user requirements into design elements, establish a relationship matrix between user requirements and design elements, and generate four conceptual design solutions based on the results. Finally, we use the PUGH decision-making method to filter and select the best concept solution for protective clothing design, and validate the design evaluation. Our results show that the protective clothing solutions designed using the combined Kano-QFD-PUGH system approach have a higher level of satisfaction compared to traditional protective clothing design. This method accurately explores the mapping relationship between user requirements and design functional elements and can be used as a general reliability design method. It helps to improve the development efficiency of designers and the decision-making role for design concept solution preference. Overall, our research methodology provides a comprehensive approach to developing medical protective clothing, which can be useful for designers and decision-makers in the healthcare industry.

PLoS ONEVol. 19(10)
Guangzhou Automobile Group (China) (CN), Guangzhou Huashang College, City University of Macau (MO)
Openalex Percentile: Top 8%
Color perception and design
3.22
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