Research on optimizing maritime logistics in petro - chemical supply chains

The high capital input, high competition characteristics of the petrochemical industry makes it one of the most challenging industries for companies to operate in. This is especially so for companies operating in Asia. These characteristics call for companies to consistently enhance their effectiven...

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Bibliographic Details
Main Author: Liu, Xiao Yang
Other Authors: Lam Siu Lee
Format: Final Year Project (FYP)
Language:English
Published: 2015
Subjects:
Online Access:http://hdl.handle.net/10356/64445
Description
Summary:The high capital input, high competition characteristics of the petrochemical industry makes it one of the most challenging industries for companies to operate in. This is especially so for companies operating in Asia. These characteristics call for companies to consistently enhance their effectiveness to manage the supply chain and increase their cost efficiency. This paper seeks to propose a mathematically guided decision making model that will optimize the maritime transportation segment of the supply chain. Also, a holistic evaluation of the supply chain with respect to the societal cost imposed by the petrochemical industry is also proposed with Singapore as a case study. Literature reviews and preliminary interviews were conducted and they have identified both literature gaps and areas of potential improvement in the real world. There are limited researches conducted in the aspect of maritime transportation and specifically in the area of ship size optimization. This paper seeks to bridge that gap through the proposed 2 stage model. The Excel Premium Solver by Frontline Systems Inc. is used to compute and optimize both the first stage revenue model as well as the second stage cost model. The revenue model provides guidance on the highest revenue generating trade pairs to deploy a company’s vessels. The cost model builds upon the pairs generated to produce the optimal sizes of vessel to deploy on those pairs, with an objective to minimize the total cost per ton-mile for a company’s fleet. Results generated from the revenue model indicate that the model is able to produce revenue maximizing pairs of ports to call based on demand and supply levels. For the cost model, it produced results on the sizes of vessel to deploy on those trade pairs based on real world constraints such a trade flow volumes and fleet constraints of companies. An evaluation on the current situation in the refinery industry in Singapore also revealed certain areas where improvement can be made to reduce the societal cost imposed. This paper concludes that further improvements to its current model is possible and it is vital for petrochemical companies to adopt an integrated and holistic approach in their efforts to optimize their operations.