Title :
A multi-view modeling methodology for modular design based on relationship constraint network
Author :
Luo, Guofu ; Xiao, Yanqiu ; Jun, Ma ; Li, Hao ; Houfang, Sun
Author_Institution :
Sch. of Mech. & Electron. Eng., Zhengzhou Univ. of Light Ind., Zhengzhou, China
Abstract :
As a systematic design method, modular design requires modeling techniques to prepare information structure for construction and evolution of product system, which generally include modeling for decomposition and that for specific design and family optimization. In this paper, a multi-view modeling methodology is proposed to prepare such an information structure based on relationship constraint network. Firstly, locations of modeling techniques are given according to the whole close-loop process of modular design, and framework of this method is given. Secondly, correlative information among elements is organized in the form of constraint network, and correlative information of product is organized into a tri-view model. Then, a tri-view model of product family is established based on modular layouts, which provides a two-way channel for decomposition and optimization of modular scheme. Finally, a case is presented to illustrate the application of the proposed approach, which proved the effectiveness of this approach.
Keywords :
constraint theory; optimisation; product design; product life cycle management; modular design; multiview modeling methodology; product correlative information; product design optimization; product family optimization; product system evolution; relationship constraint network; Collaboration; Construction industry; Design engineering; Design methodology; Design optimization; Industrial relations; Modular construction; Process design; Product design; Technological innovation; Modular design; multi-view product modeling; product family modeling; relationship constraint network;
Conference_Titel :
Industrial Engineering and Engineering Management, 2009. IE&EM '09. 16th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-3671-2
Electronic_ISBN :
978-1-4244-3672-9
DOI :
10.1109/ICIEEM.2009.5344516