• Medientyp: E-Artikel
  • Titel: Cloud Manufacturing with Fuzzy Inference System: A Supply Chain Approach to Post COVID-19 Economy
  • Beteiligte: Kolahgar, Sam; Nateghi, Mohammad; Babaghaderi, Azadeh
  • Erschienen: Macrothink Institute, Inc., 2022
  • Erschienen in: Business and Economic Research
  • Sprache: Nicht zu entscheiden
  • DOI: 10.5296/ber.v12i4.19971
  • ISSN: 2162-4860
  • Schlagwörter: General Medicine
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: <jats:p>The COVID-19 pandemic shocked the managerial team with unprecedented fluctuations in supply, demand, and transportation of goods and services. The lessons learned from the COVID-19 pandemic proved the urgent need for agility and flexibility in response to similar future crises. This paper proposes a cloud manufacturing model as a clustered supply chain approach that incorporates fuzzy inference systems to provide a platform for the post-COVID-19-economy. Cloud manufacturing is a way to standardize and increase the system’s reliability, and a fuzzy inference system is suited to deal with highly uncertain circumstances. A fuzzy inference system is integrated into a cloud manufacturing model to incorporate uncertainties related to Time, Quality, Cost, Reliability, and Availability in finding the optimum supply chain of manufacturers and service centers. The model is illustrated via a simulation in the manufacturing context. The proposed approach provides a tool to address the uncertainties and disruptions resulting from wide-scale crises such as the COVID-19 pandemic.</jats:p>
  • Zugangsstatus: Freier Zugang