Kansei Engineering in User-Centered Product Design
Summary
Kansei Engineering is an approach that translates users’ sensory and emotional responses into concrete design parameters. Rooted in Japanese industrial research, it has evolved from semantic differential surveys and quality function deployment into a rich, user-centred methodology integrating affective semantics, statistical modelling and computational intelligence. The process typically begins with the elicitation of Kansei words—descriptors of user perceptions—which are then systematically quantified and mapped to product attributes through techniques such as fuzzy logic, grey relational analysis, neural networks or genetic algorithms. Recent developments have introduced big data analytics, natural language processing and interactive evolutionary methods to capture real-world user feedback with minimal bias. Applications span consumer electronics, automotive interiors, fashion and cultural artefacts, where designers leverage predictive models to forecast emotional satisfaction, optimise form, colour and texture, and personalise experiences. By bridging the gap between subjective experience and objective engineering, this framework enhances product appeal, fosters innovation and supports global competitiveness.
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Kansei Engineering in User-Centered Product Design publication trend
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Technical terms
Kansei Engineering: A methodology for capturing and incorporating users’ emotional and sensory impressions into product design decisions.
Affective Semantics: The emotional meaning encoded in descriptive words used to characterise user perceptions.
Grey Relational Analysis: A multivariate statistical method for quantifying relationships between design factors and user responses.
Fuzzy TOPSIS: A multi-criteria decision-making technique combining fuzzy logic with distance-based ranking to prioritise design alternatives.
Natural Language Processing: Computational techniques for analysing human language to extract semantic and emotional features from text data.
References
- Evolution and Emerging Trends of Kansei Engineering: A Visual Analysis Based on CiteSpace. IEEE Access (2021).
- A quantitative aesthetic measurement method for product appearance design. Advanced Engineering Informatics (2022).
- A Novel Approach of Integrating Natural Language Processing Techniques with Fuzzy TOPSIS for Product Evaluation. Symmetry (2022).
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