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Modeling and measuring the structural complexity in assembly supply chain networks

Author

Listed:
  • Nima Hamta

    (Amirkabir University of Technology (Tehran Polytechnic)
    The State University of New York)

  • M. Akbarpour Shirazi

    (Amirkabir University of Technology (Tehran Polytechnic))

  • Sara Behdad

    (The State University of New York)

  • S.M.T. Fatemi Ghomi

    (Amirkabir University of Technology (Tehran Polytechnic))

Abstract

Complexity of assembly supply chains (ASCs) is a challenge for designers and managers, especially when ASC systems become increasingly complex due to technological developments and geographically various sourcing arrangements. One of the major challenges at the early design stage is to make decision about an appropriate configuration of ASC. This paper addresses modeling and measuring the structural complexity of ASC networks in order to establish a framework obtaining the optimal ASC configuration. Considering relationship between supply chains and assembly systems, structural complexity measures for ASC network and assembly lines inside the network are developed based on Shannon’s information entropy. This complexity model can be used to configure supply chain networks and assembly systems with robust performance. In order to generate different feasible configurations of ASCs, a four-step algorithm is proposed considering assembly sequence constraint. Finally, the optimal ASC network is obtained by comparing the total complexity values of the feasible configurations.

Suggested Citation

  • Nima Hamta & M. Akbarpour Shirazi & Sara Behdad & S.M.T. Fatemi Ghomi, 2018. "Modeling and measuring the structural complexity in assembly supply chain networks," Journal of Intelligent Manufacturing, Springer, vol. 29(2), pages 259-275, February.
    • Handle: RePEc:spr:joinma:v:29:y:2018:i:2:d:10.1007_s10845-015-1106-9
    DOI: 10.1007/s10845-015-1106-9
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    References listed on IDEAS

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    1. Sivadasan, S. & Efstathiou, J. & Calinescu, A. & Huatuco, L. Huaccho, 2006. "Advances on measuring the operational complexity of supplier-customer systems," European Journal of Operational Research, Elsevier, vol. 171(1), pages 208-226, May.
    2. Blecker, Thorsten & Kersten, Wolfgang & Meyer, Christian, 2005. "Development of an Approach for Analyzing Supply Chain Complexity," MPRA Paper 5284, University Library of Munich, Germany.
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    Cited by:

    1. Michael Vidalis & Stelios Koukoumialos & Alexandros Diamantidis & George Blanas, 2022. "Analysis of a two echelon supply chain with merging suppliers, a storage area and a distribution center with parallel channels," Operational Research, Springer, vol. 22(1), pages 703-740, March.
    2. Germán Herrera Vidal & Jairo R. Coronado-Hernández & Claudia Minnaard, 2023. "Measuring manufacturing system complexity: a literature review," Journal of Intelligent Manufacturing, Springer, vol. 34(7), pages 2865-2888, October.
    3. Vladimir Modrak & Zuzana Soltysova & Daniela Onofrejova, 2019. "Complexity Assessment of Assembly Supply Chains from the Sustainability Viewpoint," Sustainability, MDPI, vol. 11(24), pages 1-15, December.
    4. Slim Zidi & Nadia Hamani & Lyes Kermad, 2022. "New metrics for measuring supply chain reconfigurability," Journal of Intelligent Manufacturing, Springer, vol. 33(8), pages 2371-2392, December.
    5. Sena Aydoğan & Gül E. Okudan Kremer & Diyar Akay, 2021. "Linguistic summarization to support supply network decisions," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1573-1586, August.

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