Data Generation in the Hunter Valley Coal Chain –A Case Study in Capacity Assessment

摘要

The Hunter Valley Coal Chain Coordinator (HVCCC) Limited is the primary planning organisation responsible for the export of coal through the Port of Newcastle, Australia. HVCCC stakeholders include producers (mining companies), rail track owners, above rail operators, and terminal operators. The HVCCC is tasked with coordinating the activities of all the corresponding parts of the coal export supply chain so as to maximise the system effi ciency. The HVCCC also has a forward looking planning role: with demand for coal expected to double in the next decade, strategic capacity planning is a core activity for the HVCCC. Optimisation and simulation models are key aids in such activity. They are used to suggest and evaluate infrastructure expansions and operating policy changes. These models require input data in the form of shipping stems, which are arrival streams of ships at the port, together with their cargo types and composition, and date and time of arrival. Although everyone is familiar with the expression ‘garbage in equals garbage out’, relatively little research is dedicated to the issues surrounding input data generation. In this research we seek to redress this, and have developed a method for generating high quality shipping data. Shipping stems used as input should be realistic, refl ecting key characteristics of historical patterns. They should accurately represent future demand scenarios. Yet they should also have controllable parameters that can be used to test what-if scenarios, such as are required by the HVCCC to answer questions about future infrastructure or operational plans. Here we review our process for achieving this, and give a case study analysing the effects of different shipping stems on the performance of the coal chain, as measured by a capacity assessment tool. The latter is an optimisation model that takes shipping stem and infrastructure data as input, and calculates key supply chain performance metrics. The potential benefi ts of alternative demand management strategies are analysed by measuring the performance of the coal chain given different shipping stems obtained via the stem generator’s controllable parameters.