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Resilient Digital Supply Chain Twins Modelling: Simulation-based Analysis on the COVID-19 Pandemic Outbreak

Title:

Resilient Digital Supply Chain Twins Modelling: Simulation-based Analysis on the COVID-19 Pandemic Outbreak

Moazzeni, Faridoddin (2021) Resilient Digital Supply Chain Twins Modelling: Simulation-based Analysis on the COVID-19 Pandemic Outbreak. Masters thesis, Concordia University.

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Abstract

Over the past few years, Supply Chains (SC) have expanded rapidly in terms of dimensions and complexity (e.g., globalization, outsourcing, etc.). Besides, numerous practitioners and researchers proposed models mainly focused on minimizing SC’s total cost. Consequently, the potential financial advantages of reduced stock levels and inventory buffers have made SCs more vulnerable to local and global Low-Frequency High-Impact disruption risks which have long-term destructive effects. For instance, the COVID-19 pandemic outbreak has severely disturbed SCs, especially for essential products, by a sharp increase in demand and raw material supply failure. During this challenging situation, the focus should be shifted from cost minimization to SC’s survival, maximizing demand satisfaction, and minimizing delivery time. Consequently, these emerging issues have put forth the need for greater emphasis to develop resilient supply chains.
This study presents a methodological SC simulation modelling framework that enables visualizing the SC and making quick decisions by SC managers in near real-time to ensure resiliency during the disruption. The solution approach is applied as a case study in Luxxeen Co., a Canadian manufacturer of green disposable products, i.e. Toilet Tissues, which is considered an essential product.
First, we develop SC’s structural and behavioral conceptual model by customizing the SCOR reference model. Afterwards, we translate it to Discrete Event Simulation formalist and implement it using the “Arena simulation software” platform. Next, we design three COVID-19 pandemic outbreak disruption scenarios in suppliers, transportation networks, and retailers. Finally, three risk mitigation strategies (i.e., Multiple Sourcing, Changing Inventory Control Policy and Buffering) are suggested to ensure SC resiliency in terms of reliability and responsiveness performance metrics. Moreover, by conducting a comparison analysis using “Process Analyzer” and “Optquest” between these scenarios, the best set of actions are proposed for each disruption scenario.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Mechanical, Industrial and Aerospace Engineering
Item Type:Thesis (Masters)
Authors:Moazzeni, Faridoddin
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Industrial Engineering
Date:20 March 2021
Thesis Supervisor(s):Awasthi, Anjali
Keywords:Supply Chain, Supply Chain Management, Supply Chain Risk Management, Supply Chain Digital Twin, COVID-19 Pandemic Disruption Risk, Discrete Event Simulation, Scenario Analysis, Essential Product Supply Chain, SCOR Model, Case Study
ID Code:988381
Deposited By: Faridoddin Moazzeni
Deposited On:27 Oct 2022 13:51
Last Modified:27 Oct 2022 13:51

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