Benefits of backup sourcing for components in assembly systems under supply uncertainty

Wenting Pan, Kut C. So, Guang Xiao

Research output: Journal article publicationJournal articleAcademic researchpeer-review

5 Citations (Scopus)


We consider an assembly system for a final product consisting of multiple components. The assembler orders each component from its primary supplier, and one of the components is subject to supply uncertainty in which the actual available quantity for assembly is only equal to a random fraction of the order quantity. After this actual available quantity is realized but before assembly for meeting final demand, the assembler can procure additional components from some backup suppliers. We derive the optimal ordering policy under this backup sourcing strategy and analyze the benefits of using backup suppliers in mitigating the adverse effect of supply uncertainty in component procurement from the primary suppliers. Our result shows that the availability of backup supplier for the component with supply uncertainty can provide very substantial benefits to the assembler, especially when the unit cost of this component from the primary supplier is high relative to the extra unit component cost from the backup supplier for high-margin products under an operating environment of high supply uncertainty and low demand uncertainty. We further show that the availability of backup suppliers for the other components with no supply uncertainty can provide additional significant benefits to the assembler when extra unit component cost of backup supplier for the unreliable component supplier is high for low-margin products with high demand uncertainty.

Original languageEnglish
Pages (from-to)158-171
Number of pages14
JournalEuropean Journal of Operational Research
Issue number1
Publication statusPublished - 1 Oct 2022


  • Assembly systems
  • Backup sourcing
  • Procurement strategies
  • Supply chain management
  • Supply uncertainty

ASJC Scopus subject areas

  • General Computer Science
  • Modelling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management


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