• DocumentCode
    2019873
  • Title

    On the Analytical Framework of Resilient Supply-Chain Network Assessing Excursion Events

  • Author

    Bhattacharya, Arijit ; Geraghty, John ; Young, Paul

  • Author_Institution
    Enterprise Process Res. Centre, Dublin City Univ., Dublin
  • fYear
    2009
  • fDate
    25-29 May 2009
  • Firstpage
    392
  • Lastpage
    397
  • Abstract
    This paper conceptualises an analytical framework meant for resiliency of supply-chain networks by assessing excursion events. Modern supply-chain networks (SCNs) face excursion events of various kinds mainly due to uncertain and turbulent markets, catastrophes, accidents, industrial disputes/strikes in organisations and terrorism. An ldquoexcursion eventrdquo is an unpredictable event that effectively shuts-down or negatively impacts the performance of at least one node/member of a system for a relatively long amount of time. In this paper, an analytical framework has been conceptualised that prevents a SCN to propagate the effects of the ldquoexcursion eventsrdquo further and maintains the network at desired equilibrium level. The gestated quantitative decision-support approach facilitates the assessment of resilient strategies for SCNs prone to excursion events that are characterised by Low Probability of occurrence and High Impact (LPHI).
  • Keywords
    decision support systems; production management; supply chain management; analytical framework; excursion events; quantitative decision-support approach; resilient supply-chain network; Analytical models; Asia; Discrete event simulation; Electronic mail; Industrial accidents; Manufacturing industries; Manufacturing processes; Resilience; Supply chains; Virtual manufacturing; Analytical framework design; Empirical research; Excursion events; Resilient supply-chain;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Modelling & Simulation, 2009. AMS '09. Third Asia International Conference on
  • Conference_Location
    Bali
  • Print_ISBN
    978-1-4244-4154-9
  • Electronic_ISBN
    978-0-7695-3648-4
  • Type

    conf

  • DOI
    10.1109/AMS.2009.29
  • Filename
    5072018