Abstract
To improve users' accurate judgment to the functional meaning of product shape, an affordance-based adaptive immune genetic optimization of shape design method was proposed. Based on analyzing the relationship among functionality, component, shape and affordance, a hierarchical model of product shape design property was presented. By combining with the experts' suggestion, the affordance vaccines were extracted and the evaluation mechanism was optimized to reduce the subjective evaluation error, and the adaptive immune genetic algorithm was used to build innovative design. According to this method, a Computer-Aided Intelligent Product Design System (CAIPDS) was realized, the design efficiency was improved and the design result was generated automatically by using design resource fully.
| Original language | English |
|---|---|
| Pages (from-to) | 1308-1314 |
| Number of pages | 7 |
| Journal | Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS |
| Volume | 20 |
| Issue number | 6 |
| DOIs | |
| State | Published - Jun 2014 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Affordance
- Back propagation neural network
- Genetic algorithms
- Immunity
- Product design
- Shape design
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