Title: A simulation methodology for evaluating emergency sourcing strategies of a discrete part manufacturer

Authors: Christos Keramydas; Dimitris Tsiolias; Dimitrios Vlachos; Eleftherios Iakovou

Addresses: Department of Mechanical Engineering, School of Engineering, Aristotle University of Thessaloniki, P.O. Box 54124, Greece ' Department of Mechanical Engineering, School of Engineering, Aristotle University of Thessaloniki, P.O. Box 54124, Greece ' Department of Mechanical Engineering, School of Engineering, Aristotle University of Thessaloniki, P.O. Box 54124, Greece ' Department of Mechanical Engineering, School of Engineering, Aristotle University of Thessaloniki, P.O. Box 54124, Greece

Abstract: Globalisation and technological evolution associated with critical socioeconomics changes altered the traditional supply chain (SC) nature, and the corresponding risk forms. Therefore, modern SCs are vulnerable to risks, and their effects (delays and disruptions of product, money, and information flows). Whilst the nature of the overall supply disruption problem is quantitative, the vast majority of the relevant literature efforts employs a qualitative approach. In this paper we focus on the evaluation of emergency sourcing (ES) risk mitigation strategies for a discrete part manufacturer, employing a quantitative approach. Specifically, a discrete event simulation methodology is developed using the Arena™ simulation software for the measurement of risk impacts on the organisation's performance, and the evaluation of alternative emergency/dual sourcing policies in terms of the premium cost paid to the alternative emergency supplier. The optimal emergency capacity that should be contracted from the alternative supplier is computed along with the associated cost savings.

Keywords: supply chain risks; risk management; supply chain disruption; risk mitigation strategies; emergency sourcing; emergency capacity; alternative suppliers; discrete event simulation; discrete parts manufacturing; supply chain management; SCM; dual sourcing.

DOI: 10.1504/IJDATS.2015.068747

International Journal of Data Analysis Techniques and Strategies, 2015 Vol.7 No.2, pp.141 - 155

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 10 Apr 2015 *

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