Product-form design model based on genetic algorithms

Shih Wen Hsiao, Fu Yuan Chiu, Shu Hong Lu

Research output: Contribution to journalArticlepeer-review

81 Citations (Scopus)

Abstract

Industrial design attempts to enhance quality of life by designing products that meet consumer requirements. Combining concepts from various fields, including design, computer technology, aesthetics, and economics, industrial designers seek to improve quality of life by designing products that meet consumer needs. Industrial designers focus on customers' perceptions of products and their preferences for certain shapes, textures, colors, styles, linguistic variables, prices, and functions. Because new products are continuously being released, manufacturers must continually design products to satisfy customer needs to avoid displacement by market competitors. When planning strategies for marketing products to various users and consumers, managers must often consider multiple combinations of product shapes and must design products that cater to consumer tastes to minimize the risk of their products being rejected by the market. Companies with highly-skilled designers have more ideas, better and more competitive products, and shorter production times than companies with weak designers. This study analyzed product styles by applying genetic algorithms and Kansei Engineering Type II (AHP and Quantification Theory Type I). This research transforms the psychological conceptions of consumers into linguistic variables. A MATLAB program was constructed to enable designers to simulate consumer logic. The cognitive dissonance between virtual and real models was minimized by using a 3D CAD model, and the virtual model of optimum solutions in this study employed a rapid prototyping machine to generate real models efficiently. Future genetic algorithm models applying different decision theories may achieve even faster and more accurate results. Relevance to industry: Component diversification enables rapid improvement in product competitiveness. This study proposes a support model that conforms to the psychological preferences of consumers by applying a genetic algorithm method. Therefore, the model is applicable to electronic commerce websites or to other unmanned shops.

Original languageEnglish
Pages (from-to)237-246
Number of pages10
JournalInternational Journal of Industrial Ergonomics
Volume40
Issue number3
DOIs
Publication statusPublished - 2010 May 1

All Science Journal Classification (ASJC) codes

  • Human Factors and Ergonomics
  • Public Health, Environmental and Occupational Health

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