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Research Papers: Design Theory and Methodology

Function Module Partition for Complex Products and Systems Based on Weighted and Directed Complex Networks

[+] Author and Article Information
Yupeng Li

Department of Industrial Engineering,
Key Laboratory of Deep Coal Resource Mining,
Ministry of Education of China,
School of Mines,
China University of Mining and Technology,
Xuzhou 221116, Jiangsu, China
e-mail: ypeng_li@163.com

Zhaotong Wang

Department of Industrial Engineering,
China University of Mining and Technology,
Xuzhou 221116,
Jiangsu, China
e-mail: cumtwzt@163.com

Lei Zhang

School of Mechanical Engineering,
Shanghai Jiao Tong University,
Shanghai 200240, China
e-mail: zhanglei415@sjtu.edu.cn

Xuening Chu

School of Mechanical Engineering,
Shanghai Jiao Tong University,
Shanghai 200240, China
e-mail: xnchu@sjtu.edu.cn

Deyi Xue

Department of Mechanical and
Manufacturing Engineering,
University of Calgary,
Calgary, AB T2N 1N4, Canada
e-mail: dxue@ucalgary.ca

1Corresponding authors.

Contributed by the Design Theory and Methodology Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received May 15, 2016; final manuscript received October 11, 2016; published online November 14, 2016. Assoc. Editor: Kristina Shea.

J. Mech. Des 139(2), 021101 (Nov 14, 2016) (13 pages) Paper No: MD-16-1359; doi: 10.1115/1.4035054 History: Received May 15, 2016; Revised October 11, 2016

Modular design is an effective approach to shorten lead-time and reduce cost for development of complex products and systems (CoPS). Because the physical details of the product are not available at the conceptual design stage, considerations in the downstream product development phases such as manufacturing and assembly cannot be used for partition of modules at the conceptual design stage. Since design solution at the conceptual design stage can be modeled by functions and relationships among these functions such as function flows including information flows, material flows, and energy flows, a novel approach is introduced in this research for function module partition of CoPS through community detection using weighted and directed complex networks (WDCN). First, the function structure is obtained and mapped into a weighted and directed complex network. Based on the similarity between behaviors of communities in WDCN and behaviors of modules in CoPS, a LinkRank-based community detection approach is employed for function module partition through optimization with simulated annealing. The function module partition for the power mechanism in a large tonnage crawler crane is conducted as a case study to demonstrate the effectiveness of the developed approach.

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Figures

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Fig. 1

Graphical representations of several typical complex networks: (a) undirected and unweighted complex network, (b) direct complex network, and (c) weighted complex network

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Fig. 2

Complex networks with different modularity measures: (a) a complex network with good modularity and (b) a complex network with poor modularity

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Fig. 3

A directed network

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Fig. 4

Functional model for a refrigeration process

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Fig. 5

Topological structure of the function model for a refrigeration process

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Fig. 6

The identification process of weights of edges: (a) two nodes have edges pointing the same direction and (b) two nodes have edges pointing different directions

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Fig. 8

The process of LRC

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Fig. 9

A large tonnage crawler crane

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Fig. 10

The black box model for the power mechanism of LTCC

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Fig. 11

The functional model for the power mechanism of LTCC

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Fig. 12

The WCDN of the function model for the LTCC

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Fig. 13

The function module partition scheme for the power mechanism of LTCC

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Fig. 14

The function modules of power mechanism obtained by the LRC algorithm: (a) power source module, (b) lifting module, (c) Luffing module, (d) rotation module, (e) traveling module, and (f) the group of C6–C9 represents the cooling module of the power mechanism

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Fig. 15

A snapshot of the execution messages of the optimization program

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Fig. 16

The module partition scheme obtained by the heuristic method proposed by Stone et al. [15]

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