A method for product form design of integrating interactive genetic algorithm with the interval hesitation time and user satisfaction
Due to the continuous release of new products, manufacturers are paying attention to customer-oriented design of products that meet user needs to minimize the risk of their products being rejected by the market. Due to the ambiguity of user cognition, it is difficult to accurately obtain the user�...
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| Published in: | International journal of industrial ergonomics Vol. 76; p. 102901 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
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Amsterdam
Elsevier B.V
01.03.2020
Elsevier BV |
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| ISSN: | 0169-8141, 1872-8219 |
| Online Access: | Get full text |
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| Abstract | Due to the continuous release of new products, manufacturers are paying attention to customer-oriented design of products that meet user needs to minimize the risk of their products being rejected by the market. Due to the ambiguity of user cognition, it is difficult to accurately obtain the user's preference for individual productions. To respond to the challenge, we propose an engineering scientific research method of interactive genetic algorithm with the interval arithmetic based on hesitation and fuzzy kano model(FKM) to explore the emotional needs of users for product forms and drive product modeling evolution design. Through expert interviews, the morphological characteristics and perceptual images factors of the products attracting users are investigated. In order to identify the user's satisfaction relationship with the perceptual images, we use FKM to analyze the product image style that meets the user's kansei needs accurately and selects 5 factors which is attractive attributes. Meanwhile, we attempt to transform this 5 factors into evaluation carrier to guide the evolution direction of product styling in HIIF-IGA, and then optimized four electric bikes with scores over 8.8 so that it could realize user demand-driven product evolution design. To handle users' ambiguity, the FAHP method is used to quantify the user's emotional imagery criterion and create a product evolution design system platform, which can automatically generate product styling design scheme in line with user preferences. This experimental results show that the proposed method can help enterprises effectively improve customer satisfaction and reduce the cost and time of product development.
•Accurately extracting kansei images and modeling attractiveness factors of productions based on user psychological need.•User's perceptual demand for products is identified and transformed into the basis of the fitness evaluation of IGA.•Constructing a small modeling database, which can accelerate the convergence during evolution process.•The interval hesitation time value is used to represent the individual fitness value.•A product design system is developed to verify the method's effectiveness. |
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| AbstractList | Due to the continuous release of new products, manufacturers are paying attention to customer-oriented design of products that meet user needs to minimize the risk of their products being rejected by the market. Due to the ambiguity of user cognition, it is difficult to accurately obtain the user's preference for individual productions. To respond to the challenge, we propose an engineering scientific research method of interactive genetic algorithm with the interval arithmetic based on hesitation and fuzzy kano model(FKM) to explore the emotional needs of users for product forms and drive product modeling evolution design. Through expert interviews, the morphological characteristics and perceptual images factors of the products attracting users are investigated. In order to identify the user's satisfaction relationship with the perceptual images, we use FKM to analyze the product image style that meets the user's kansei needs accurately and selects 5 factors which is attractive attributes. Meanwhile, we attempt to transform this 5 factors into evaluation carrier to guide the evolution direction of product styling in HIIF-IGA, and then optimized four electric bikes with scores over 8.8 so that it could realize user demand-driven product evolution design. To handle users' ambiguity, the FAHP method is used to quantify the user's emotional imagery criterion and create a product evolution design system platform, which can automatically generate product styling design scheme in line with user preferences. This experimental results show that the proposed method can help enterprises effectively improve customer satisfaction and reduce the cost and time of product development. Due to the continuous release of new products, manufacturers are paying attention to customer-oriented design of products that meet user needs to minimize the risk of their products being rejected by the market. Due to the ambiguity of user cognition, it is difficult to accurately obtain the user's preference for individual productions. To respond to the challenge, we propose an engineering scientific research method of interactive genetic algorithm with the interval arithmetic based on hesitation and fuzzy kano model(FKM) to explore the emotional needs of users for product forms and drive product modeling evolution design. Through expert interviews, the morphological characteristics and perceptual images factors of the products attracting users are investigated. In order to identify the user's satisfaction relationship with the perceptual images, we use FKM to analyze the product image style that meets the user's kansei needs accurately and selects 5 factors which is attractive attributes. Meanwhile, we attempt to transform this 5 factors into evaluation carrier to guide the evolution direction of product styling in HIIF-IGA, and then optimized four electric bikes with scores over 8.8 so that it could realize user demand-driven product evolution design. To handle users' ambiguity, the FAHP method is used to quantify the user's emotional imagery criterion and create a product evolution design system platform, which can automatically generate product styling design scheme in line with user preferences. This experimental results show that the proposed method can help enterprises effectively improve customer satisfaction and reduce the cost and time of product development. •Accurately extracting kansei images and modeling attractiveness factors of productions based on user psychological need.•User's perceptual demand for products is identified and transformed into the basis of the fitness evaluation of IGA.•Constructing a small modeling database, which can accelerate the convergence during evolution process.•The interval hesitation time value is used to represent the individual fitness value.•A product design system is developed to verify the method's effectiveness. |
| ArticleNumber | 102901 |
| Author | Wang, Tianxiong Zhou, Meiyu |
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| Keywords | Fuzzy kano model Customer demand User fatigue Interactive genetic algorithm User preference |
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| Snippet | Due to the continuous release of new products, manufacturers are paying attention to customer-oriented design of products that meet user needs to minimize the... |
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| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
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| SubjectTerms | Algorithms Ambiguity Bicycles Cognition Customer demand Customer satisfaction Design Emotions Evolution Fuzzy kano model Genetic algorithms Imagery Immunoglobulin A Interactive genetic algorithm Interval arithmetic Physical characteristics Product design Product development Product image Product modelling Risk reduction Styling User fatigue User preference User satisfaction |
| Title | A method for product form design of integrating interactive genetic algorithm with the interval hesitation time and user satisfaction |
| URI | https://dx.doi.org/10.1016/j.ergon.2019.102901 https://www.proquest.com/docview/2442321040 |
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