Full Text:   <1811>

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CLC number: TH122

On-line Access: 2016-04-05

Received: 2015-06-03

Revision Accepted: 2015-10-10

Crosschecked: 2016-03-08

Cited: 0

Clicked: 3123

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Yi-xiong Feng

http://orcid.org/0000-0001-7397-2482

Hao Zheng

http://orcid.org/0000-0003-3259-9153

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Journal of Zhejiang University SCIENCE A 2016 Vol.17 No.4 P.286-294

http://doi.org/10.1631/jzus.A1500161


An integrated cognitive computing approach for systematic conceptual design


Author(s):  Hao Zheng, Yi-xiong Feng, Jian-rong Tan, Zhi-feng Zhang, Zi-xian Zhang

Affiliation(s):  State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China; more

Corresponding email(s):   fyxtv@zju.edu.cn

Key Words:  Conceptual design, Cognitive computing, Genetic algorithm (GA), Technique for order preference by similarity to ideal solution (TOPSIS)


Hao Zheng, Yi-xiong Feng, Jian-rong Tan, Zhi-feng Zhang, Zi-xian Zhang. An integrated cognitive computing approach for systematic conceptual design[J]. Journal of Zhejiang University Science A, 2016, 17(4): 286-294.

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Abstract: 
conceptual design plays an important role in product life cycle, which requires engineers to use sound design theory, cross-disciplinary knowledge, and complex technical support to acquire design concepts. However, the lack of sufficient computational tools makes it difficult for designers to fully explore in the wide design solution spaces. Therefore, this paper proposes an integrated cognitive computing approach to formalize the cognitive activities of conceptual design. A cognitive computing model composed of concept associative memory, concept generation, and decision-making process is established based on the integration of cognitive psychology and engineering design. First of all, the Hopfield neural network is used to acquire similar concept solutions for specific subfunctions from a knowledge base. Then, morphological matrix and genetic algorithm are introduced to produce a set of feasible candidate solutions in the concept generation process. Furthermore, a technique for order preference by similarity to an ideal solution is applied to evaluate the generated concept solutions and obtain the optimal solution automatically. Finally, a case study is given to demonstrate the effectiveness and efficiency of the proposed approach.

Overall the paper is good. It describes an interesting design issue about creativity during the conceptual design phase. It presents a methodology which can help designers to consider alternative designs.

一种面向系统化概念设计的集成认知计算方法

目的:产品概念设计是一种复杂的认知活动过程,在产品生命周期中具有极其重要的作用。目前对产品概念设计的智能化方向主要集中在概念生成与评价等离散阶段,尚缺乏系统性的智能化概念设计方法。本文的目的是在形式化与系统化概念设计过程中,实现设计的计算化与智能化,支持计算机辅助设计的发展与应用。
创新点:1. 结合工程设计与认知科学,提出多阶段设计认知模型表达产品设计过程;2. 采用计算智能算法,实现设计认知模型的智能求解。
方法:1. 通过分析设计者的设计过程规律,结合认知心理学构建符合设计流程的多阶段设计认知模型(图1);2. 通过引入计算智能算法,分别对认知模型中概念联想、概念组合和方案评价进行认知计算,实现设计过程的正向求解(图2);3. 通过仿真模拟,运用认知计算方法对液压机产品进行概念设计求解,得到相关的设计方案,并验证所提方法的可行性和有效性(表3)。
结论:1. 产品概念设计过程可抽象为概念生成、概念组合和方案评价的认知过程;2. 认知过程可以引入计算智能方法对其进行分别模拟计算;3. 运用认知计算方法对产品进行概念设计,可以显著提高设计效率,同时有助于设计自动化的实现。

关键词:概念设计;认知计算;遗传算法;优劣解距离法

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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