Integration of axiomatic design and design structure matrix for the modular design of automobile parts
- Authors
- Park, S.-O.; Yoon, J.; An, H.; Park, J.; Park, G.-J.
- Issue Date
- Feb-2022
- Publisher
- SAGE Publications Ltd
- Keywords
- Axiomatic design; cooling system; design structure matrix; modular design; suspension system
- Citation
- Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, v.236, no.3, pp 296 - 306
- Pages
- 11
- Indexed
- SCIE
SCOPUS
- Journal Title
- Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture
- Volume
- 236
- Number
- 3
- Start Page
- 296
- End Page
- 306
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/105753
- DOI
- 10.1177/09544054211014484
- ISSN
- 0954-4054
2041-1975
- Abstract
- As the demands of customers in the modern industry increased, the number of products, and the variety of components has increased. These issues have led to difficulties in product development and production. Modularization of products has advantages such as cost reduction, product development time reduction, and production time reduction. Modular design of products has been studied in the design activities of the modern industry. In this study, a modular design method is proposed to design a modular product based on axiomatic design (AD) and design structure matrix (DSM). AD and DSM are efficiently integrated into the proposed method. Functional requirements and design parameters are defined based on the Independence Axiom of AD, and the zigzagging process of AD is employed for the decomposition of the functional requirements (FRs) and design parameters (DPs). The design sequence is established based on the design matrix. Coupled or functionally close DPs are grouped into a module (Module 1). These modules are efficiently used in the design sequence. DSM is used to modularize the design parameters of the lowest level of axiomatic design. DSM is constructed based on physical interfaces and numerical clustering algorithms are used to identify strongly related components. They are grouped into a module (Module 2). Module 2 is exploited for production and management. Therefore, these two modules for different purposes can be used to increase efficiency in the design and production process. The proposed method is applied to two automobile parts such as the suspension system and cooling system. The results are discussed from the viewpoint of usefulness. © IMechE 2021.
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