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Research Papers: Design Automation

Analysis of Architectural Complexity for Product Family and Platform

[+] Author and Article Information
Gwang Kim

Department of Industrial Engineering,
Seoul National University,
1 Gwanak-ro, Gwanak-gu,
Seoul 08826, Korea
e-mail: gwangkim91@snu.ac.kr

Yunjung Kwon

Department of Industrial Engineering,
Seoul National University,
1 Gwanak-ro, Gwanak-gu,
Seoul 08826, Korea
e-mail: yunjungkwon@snu.ac.kr

Eun Suk Suh

Department of Industrial Engineering,
Seoul National University,
1 Gwanak-ro, Gwanak-gu,
Seoul 08826, Korea
e-mail: essuh@snu.ac.kr

Jaemyung Ahn

Department of Aerospace Engineering,
Korea Advanced Institute of Science
and Technology (KAIST),
Daejeon 305-701, Korea
e-mail: jaemyung.ahn@kaist.ac.kr

1Corresponding author.

Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received October 14, 2015; final manuscript received April 9, 2016; published online May 16, 2016. Assoc. Editor: Carolyn Seepersad.

J. Mech. Des 138(7), 071401 (May 16, 2016) (11 pages) Paper No: MD-15-1705; doi: 10.1115/1.4033504 History: Received October 14, 2015; Revised April 09, 2016

A product family is a set of products that are derived from common sets of parts, interfaces, and processes, known as the product platform. To reduce development time and procurement and operating costs of product platform-based variants, the product platform can be designed after consideration of several characteristics, such as modularity, flexibility, sustainability, and complexity. In this paper, the product platform is viewed from the perspective of system architecting. The architectural complexities of both the platform and its variants, which together constitute a product family, can be quantitatively assessed using a specifically tailored metric. This will aid system architects in designing product platforms and resulting product variants with an emphasis on reducing complexity. Architectural complexity management is demonstrated through a case study of a train bogie platform.

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Figures

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Fig. 3

DSM of p1 with physical connections, mass flows, energy flows, and the information flows separated

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Fig. 2

Representation of product platform and variants in DSM format

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Fig. 1

Proposed process overview

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Fig. 7

Trailing bogie DSM (physical connection)

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Fig. 4

Tilting mechanism for the train (with permission from KRRI)

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Fig. 5

Tilting train developed by KRRI Consortium (with permission from KRRI)

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Fig. 6

CAD drawings of bogies (with permission from KRRI)

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Fig. 8

Structural complexity values for bogies and the platform

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Fig. 9

Flow complexity values for bogies and the platform

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