Enterprises with a global supply network are at risk of lost revenue as a result of disruptive disasters at supplier locations. Various strategies exist for addressing this risk, and a variety of types of research has been done regarding the identification, assessment and response to the risk of disruption in a supply chain network.
This thesis establishes a decision model to support Business Continuity Planning at the first-tier supplier level. The decision model incorporates discrete-event simulation of supply chain networks (through Simio software), Monte Carlo simulation, and risk index optimization. After modeling disruption vulnerability in a supply chain network, costs of implementing all combinations of Business Continuity Plans are ranked and then tested in discrete-event simulation for further insight into inventory levels, unmet customer demand, production loss and related costs.
A case study demonstrates the implementation of the decision support process and tests a historical set of data from a large manufacturing company. Discrete-event simulation modeling of loss is confirmed to be accurate. The relevance of the model concept is upheld and recommendations for future work are made.
Identifer | oai:union.ndltd.org:CALPOLY/oai:digitalcommons.calpoly.edu:theses-2818 |
Date | 01 March 2016 |
Creators | Mosunich, Marissa Anne |
Publisher | DigitalCommons@CalPoly |
Source Sets | California Polytechnic State University |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Master's Theses |
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