Identification of key design characteristics for complex products adaptive design

Han, Xin, Li, Rong, Wang, Jian, Qin, Sheng-feng and Ding, Guofu (2018) Identification of key design characteristics for complex products adaptive design. International Journal of Advanced Manufacturing Technology, 95 (1-4). pp. 1215-1231. ISSN 0268-3768

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Official URL: https://doi.org/10.1007/s00170-017-1267-0

Abstract

Key design characteristics (KDCs) are important information related to the product and part designs, which significantly influence on the product's functions, performances, and quality. Identifying KDCs for a complex productwill help designers to focus on key design parameters during the design process and rapidly obtain design schemes based on their close relationships to the product's functions, performances, and quality. Although there are some researches on key characteristic (KC) identification, most of them are focusedon key process characteristics (KPCs) and few on KDCs. There also lacks a KDC identification framework to support KDC identification with better completeness and diverse usages. Adaptive design is the most important pattern of complex product design. Therefore, this paper presents a systematic method to identify KDCs for complex product adaptive design, in which KDCs can be determined by two related phases. Firstly, a product design specification (PDS)-KDC Candidates Network (PKCN) is constructed by using existing product instance data, cluster analysis, KC flow-down, and network analysis approaches. Then, the result from the first phase is used as a basis to identify KDCs for adaptive design. Three KDC identification techniques: similarity reasoning technique, breadth-first search (BFS), and the gray relational analysis approach are applied to find out KDCs from the PKCN, which are the most sensitive to the variation of a PDS. These identified KDCs can help designers to understand the relationships between KDCs and PDS and rapidly develop a design scheme. The effectiveness and the feasibility of the proposed method are verified by a case study via the development of an electric multiple unit (EMU)'s bogie.

Item Type: Article
Uncontrolled Keywords: Identification of key design characteristics, Gray relational analysis, Systematic approach, Complex products, Adaptive design, network analysis
Subjects: H900 Others in Engineering
W200 Design studies
Department: Faculties > Arts, Design and Social Sciences > Design
Depositing User: Ellen Cole
Date Deposited: 09 Nov 2017 15:34
Last Modified: 31 Jul 2021 14:50
URI: http://nrl.northumbria.ac.uk/id/eprint/32498

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