Identifying Optimal Granularity Level of Modular Assembly Supply Chains based on Complexity-Modularity Trade-off

Bugra Alkan, Seth Bullock, Kevin Galvin

Research output: Contribution to journalArticle (Academic Journal)peer-review

3 Citations (Scopus)
85 Downloads (Pure)

Abstract

Complexity has been argued to limit operational efficiency, hinder decision-making and induce disruption in supply chain networks. The main aim of this paper is to investigate the architectural trade-off between complexity and modularity in modular assembly supply chain networks. Towards this, an information-entropic complexity model is adopted to the domain of assembly supply chains and logistics. The approach describes complexity as a combination of the intrinsic complexity of the system modules/interfaces and the influence of the topological composition of the network. The mathematical model is then used in the optimisation framework, where the optimal granularity level for assembly supply chain design solutions for a given assembly product can be automatically verified by considering the trade-off between complexity and network modularity. It is concluded that the methodology could help to minimise the complexity of the supply chain assembly configurations while maximising their modularity and thereby help to increase both the reliability and performance of supply chain networks.
Original languageEnglish
Article number9402733
Pages (from-to)57907-57921
Number of pages15
JournalIEEE Access
Volume9
DOIs
Publication statusPublished - 13 Apr 2021

Bibliographical note

Funding Information:
This work was supported in part by the Thales Group and the University of Bristol, in part by the U.K. Engineering and Physical Sciences Research Council Research Grant Award entitled Thales-Bristol Partnership in Hybrid Autonomous Systems Engineering (T-B PHASE) under Grant EP/R004757/1, and in part by the open access fee through the University of Bristol.

Publisher Copyright:
© 2013 IEEE.

Keywords

  • Complexity theory
  • Assembly systems
  • Supply chain management
  • Network theory (graphs)
  • Pareto optimization

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