Customer-oriented product collaborative customization based on design iteration for tablet personal computer configuration. (September 2016) - Dou, Runliang; Zhang, Yubo; Nan, Guofang
Graphical abstract: The existing products and the increasing design schemes can be fully organized as valuable knowledge to iteratively improve later design process through the design iteration-based approach using IGA. A system prototype is developed based the approach with a GUI whose 'single click' interactive mode without slides or input boxes relieves user fatigue. With the help of the system, a case study for tablet PC design is given, which verified the effectiveness. Highlights: An approach based on design iteration for product customization with the benefit of IGA. Extending product family concept to design family concept. A system prototype is developed based on the approach with a GUI. A case study for tablet PC design verified the effectiveness of the proposed approach. Abstract: Customers limited knowledge and technique restrains manufacturer from making them directly participate in practical product design to quickly respond to their complex and personalized demand. Based on design iteration, an approach to customer-oriented product collaborative customization is proposed for manufacturer to improve the design process. This approach uses the existing product and continuously increasing product design scheme as valuable product configuration knowledge. Meanwhile, the concept of product family is extended to design family, where the product individual and design scheme are respectively distributed into different knowledge bases. With the benefit of iterative genetic algorithm (IGA), design iteration is applied to make the existing product and design process bi-directionally evolve in the customized process to seek the optimal design, accordingly customers' operational fatigue will be lessened and their customized efficiency will be improved. Finally, the customized design of tablet PC is taken for instance to testify the maneuverability and effectiveness of the proposed approach. The experimental results demonstrate that the approach could effectively identify customers' preference and obviously improve their customization efficiency, with lessening their operational fatigue to the large extent.