A fuzzy-based integrated framework for supply chain risk assessment

Faisal Aqlan, Sarah S. Lam

Research output: Contribution to journalArticlepeer-review

97 Scopus citations

Abstract

This research presents an integrated framework for supply chain risk assessment. The framework consists of three main components: survey, Bow-Tie analysis, and fuzzy inference system (FIS). The survey component consists of questionnaires used to identify the risk factors and their likelihoods and impacts. Potential risks are identified based on experts' knowledge, historical data, and supply chain structure. The identified risks are measured by aggregating the estimated values of risk parameters. Bow-Tie, which is a diagram that displays the links between potential causes, preventative and mitigative controls and consequences of a risk, is used to calculate the aggregated likelihood and impact of the risk. FIS is then used to calculate the total risk score considering the risk management parameters and risk predictability. A case study from a high-end server manufacturing environment is considered. For the two main product types produced by the company, risks are assessed and aggregated per product type. Given the individual and aggregated risk scores, decision makers can either perform top-down or bottom-up risk analysis and focus on the significant risks that could affect their business operations.

Original languageEnglish (US)
Pages (from-to)54-63
Number of pages10
JournalInternational Journal of Production Economics
Volume161
DOIs
StatePublished - Mar 1 2015

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting(all)
  • Economics and Econometrics
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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