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Research Papers

Concurrent Design of Assembly Plans and Supply Chain Configurations Using AND/OR Graphs and Dynamic Programing

[+] Author and Article Information
Heng Kuang

Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109
e-mail: hekuang@umich.edu

S. Jack Hu

Mechanical Engineering,
University of Michigan,
Ann Arbor, MI 48109
e-mail: jackhu@umich.edu

Jeonghan Ko

Industrial & Operations Engineering,
University of Michigan,
Ann Arbor, MI 48109;
Department of Industrial Engineering,
Ajou University,
Suwon 16499, Korea
e-mails: jeonghan@umich.edu; jko@ajou.ac.kr

1Corresponding author.

Manuscript received June 29, 2014; final manuscript received September 17, 2015; published online January 4, 2016. Assoc. Editor: Jianjun Shi.

J. Manuf. Sci. Eng 138(5), 051011 (Jan 04, 2016) (9 pages) Paper No: MANU-14-1351; doi: 10.1115/1.4032027 History: Received June 29, 2014; Revised September 17, 2015

Making concurrent decisions on assembly plans and supply chain configurations (SCCs) is a desirable strategy in today's competitive global market. Such concurrent decisions help reduce decision iterations for shortened lead time and lower the total cost for manufacturers and their supply chains. However, there lacks deep understanding of the interaction between assembly plans and SCCs, as well as methodologies for integrating them. In this paper, we consider an assembly planning problem that simultaneously decomposes an assembly product to modules and assigns the modules to suppliers. The joint decision is formulated as an optimization problem of finding the assembly decomposition and the corresponding supply chain network with the lowest total supply chain cost. We develop a coordinated decision-making method by integrating assembly AND/OR graphs with supply chain cost information. A dynamic programing (DP) based algorithm is developed to efficiently solve the combined optimization problem. Case studies demonstrate that the proposed method can find optimal solutions for the integrated decision-making problem efficiently and provide a tool to plan assemblies from the perspective of the total supply chain cost in the early stages of product development.

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References

Figures

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Fig. 2

Liaison graph of the pen, adapted from Ref. [34]

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Fig. 3

Transportation flows of the two assembly plans: (a) assembly plan I and (b) assembly plan II

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Fig. 1

A pen example: assembly and its components, adapted from Ref. [34]

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Fig. 4

AND/OR graph of the pen example

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Fig. 5

An example of an assembly plan

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Fig. 6

An example hyper AND/OR graph for the pen example

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Fig. 7

An instance of assembly plan with supplier assignment

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Fig. 8

Assembly plans of the pen

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Fig. 12

The optimal assembly plan with supplier assignment

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Fig. 13

The material flow of the optimal assembly and supply chain plan

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Fig. 14

The optimal assembly plan with supplier assignment: under supply chain with increased display price in country 2

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Fig. 9

Laptop and the liaison graph, adapted from Ref. [35]

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Fig. 10

Precedence graph of the laptop, adapted from Ref. [35]

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Fig. 11

A part of the AND/OR graph of the laptop

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