Literature DB >> 33628216

Intelligent Design of Product Forms Based on Design Cognitive Dynamics and a Cobweb Structure.

Wenjin Yang1, Jian-Ning Su1,2, Shutao Zhang2, Kai Qiu1, Xinxin Zhang3.   

Abstract

Design is a complex, iterative, and innovative process. By traditional methods, it is difficult for designers to have an integral priori design experience to fully explore a wide range of design solutions. Therefore, refined intelligent design has become an important trend in design research. More powerful design thinking is needed in intelligent design process. Combining cognitive dynamics and a cobweb structure, an intelligent design method is proposed to formalize the innovative design process. The excavation of the dynamic mechanism of the product evolution process during product development is necessary to predict next-generation multi-image product forms from a larger design space. First, different design thinking stimulates the information source and is obtained by analyzing the designers' thinking process when designing and mining the dynamic mechanism behind it. Based on the nonlinear cognitive cobweb process proposed by Francisco and a natural cobweb structure, the product image cognitive cobweb model (PICCM) is constructed. Then, natural cobweb predation behavior is simulated using a stimulus information source to impact the PICCM. This process uses genetic algorithms to obtain numerous offspring forms, and the PICCM's mechanical properties are the energy loss parameters in the impact information. Furthermore, feasible solutions are selected from intelligent design sketches by the product artificial form evaluation system based on designers' cognition, and a new product image cognitive cobweb system is reconstructed. Finally, a case study demonstrates the efficiency and feasibility of the proposed approach.
Copyright © 2021 Wenjin Yang et al.

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Year:  2021        PMID: 33628216      PMCID: PMC7889380          DOI: 10.1155/2021/6654717

Source DB:  PubMed          Journal:  Comput Intell Neurosci


  3 in total

1.  The dynamical integrity concept for interpreting/ predicting experimental behaviour: from macro- to nano-mechanics.

Authors:  Stefano Lenci; Giuseppe Rega; Laura Ruzziconi
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2013-05-20       Impact factor: 4.226

2.  Philosophy for the rest of cognitive science.

Authors:  Nigel Stepp; Anthony Chemero; Michael T Turvey
Journal:  Top Cogn Sci       Date:  2011-04

Review 3.  Combining Grey Relationship Analysis and Neural Network to Develop Attractive Automobile Booth Design.

Authors:  Xinhui Kang
Journal:  Comput Intell Neurosci       Date:  2020-06-20
  3 in total

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