E. Sönmez; "Model-Based Analysis of Liquefied Natural..", Jan.14,13:40
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  • E. Sönmez; "Model-Based Analysis of Liquefied Natural..", Jan.14,13:40

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FENS IE Seminar

Model-based Analysis of Liquefied Natural Gas Regasification Technologies

Erkut Sönmez, Carnegie Mellon University

The liquefied natural gas (LNG) industry is growing on a worldwide scale driven by a basic geographical mismatch between the supply and demand of natural gas. This growth is spurring investment throughout the entire global LNG supply chain; in this paper we study investment in regasification and shipping capacity. There are two main types of LNG regasification technologies: Onshore at a land based terminal and offshore onboard specialized vessels that also transport LNG. We refer to the former technology as onshore-terminal and to the latter as offshore-onboard. The offshore-onboard technology is a rather recent development, with the first such facility having become operational only in 2005.

In this study, we develop queueing and simulation models of LNG supply chains that use these two types of regasification technologies. By applying these models to a realistic case, we bring to light two main drivers of this technology adoption choice: The time-to-revenue advantage and the volume. By crossing these two dimensions we derive four predictions as to when each technology should be adopted. Further, we find that when offshore-onboard technology should be adopted, it should be configured using a dedicated, as opposed to a mixed, fleet of vessels. Our predictions are potentially amenable to future empirical testing and validation, and provide principles for guiding decisions in the LNG industry. Our analysis has potential relevance to a broader class of technology adoption problems. Biography

Erkut Sönmez is currently a PhD candidate in the area of operations management in Tepper School of Business at Carnegie Mellon University. He obtained his BS degree in Industrial Engineering at Middle East Technical University in 2004. He received his MS degree in Industrial Administration at Tepper School of Business, Carnegie Mellon University in 2006. In his research, he has studied capacity choice problems that arise with the development of new technologies, including specific applications in the banking and energy sectors. His research interests include stochastic modeling, queueing theory and multidisciplinary work at the interface of operations management and other disciplines such as economics, finance and marketing, both in theoretical and empirical directions.

Wednesday, 14 January 2009, 13:40-14:30,  FENS 2072