Cloud Manufacturing with Fuzzy Inference Systems: A Supply Chain Approach to Post Covid-19 Economy

39 Pages Posted: 7 Sep 2021

See all articles by Sam Kolahgar

Sam Kolahgar

University of Prince Edward Island, Faculty of Business

Mohammad Nateghi

Independent

Azadeh Babaghaderi

University of Windsor

Date Written: September 6, 2021

Abstract

This paper proposes a cloud manufacturing model as a supply chain approach for the post-COVID-19-economy. A fuzzy inference system is integrated into the model to optimally manage uncertainties related to Time, Quality, Cost, Reliability, and Availability caused by disruptions in the supply chain. The paper illustrates the implication of the model using a simulation in the context of a manufacturing process. The proposed model seeks to satisfy customers’ demands for high-quality products and services, in a timely manner, at the lowest cost possible. These properties are necessary in times of disruptions such as the COVID-19 pandemic and the like.

Keywords: Pandemic, COVID-19, Cloud Manufacturing, Cloud Computing, Clustered Supply Chain, Fuzzy Inference System, Deductive Fuzzy Logic

Suggested Citation

Kolahgar, Sam and Nateghi, Mohammad and Babaghaderi, Azadeh, Cloud Manufacturing with Fuzzy Inference Systems: A Supply Chain Approach to Post Covid-19 Economy (September 6, 2021). Available at SSRN: https://ssrn.com/abstract=3918522 or http://dx.doi.org/10.2139/ssrn.3918522

Sam Kolahgar (Contact Author)

University of Prince Edward Island, Faculty of Business ( email )

Charlottetown, P.E.I. C1A 4P3
Canada

Mohammad Nateghi

Independent ( email )

Azadeh Babaghaderi

University of Windsor ( email )

401 Sunset
Windsor N9B 3P4, Ontario
Canada

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