School of Art, Yulin University of Shaanxi Province, Yulin 719000, China.
Comput Intell Neurosci. 2022 Aug 21;2022:6339184. doi: 10.1155/2022/6339184. eCollection 2022.
People are becoming more and more aware of the value of design throughout a product's entire life cycle as a result of the fierce competition for industrial products that exists today. The life of a product involves its design, manufacture, sale, and use, and how well these links are managed determines the product's positioning in terms of value in the eyes of consumers. The key to the functional integration of the design is monitoring the entire process and applying the user's emotional needs. A useful tool for assessing users' emotional needs is the perceptual image of a product. An artificial intelligence-driven method for product perceptual design is proposed, and its efficacy is demonstrated by the design of an optometer. This method addresses the issues of incomplete measurement and insufficient sample collection in the traditional users' perceptual cognition measurement. The findings demonstrate that extracting users' perceptual cognition through text mining can assist designers in better understanding users' perceptual needs, resulting in designed products that are more likely to meet users' expectations for satisfaction. A design approach that can increase users' psychological acceptance of products and boost their competitiveness is the perceptual design method, which combines human and artificial intelligence.
由于当今工业产品竞争激烈，人们越来越意识到产品整个生命周期内设计的价值。产品的生命周期包括设计、制造、销售和使用，这些环节的管理好坏决定了产品在消费者眼中的价值定位。设计的功能集成关键在于监控整个过程并应用用户的情感需求。评估用户情感需求的有用工具是产品的感性形象。提出了一种基于人工智能的产品感性设计方法，并通过设计一款验光仪验证了其有效性。该方法解决了传统用户感性认知测量中测量不完整和样本采集不足的问题。研究结果表明，通过文本挖掘提取用户的感性认知，可以帮助设计师更好地理解用户的感性需求，从而设计出更符合用户满意度预期的产品。一种能够提高用户对产品的心理接受度并提高产品竞争力的设计方法是结合了人和人工智能的感性设计方法。
