444454 Facilitating Real-Time Decision-Making of Marine Terminal Operations

Tuesday, April 12, 2016: 8:00 AM
336B (Hilton Americas - Houston)
Intan Hamdan, Chemical Engineering, The Dow Chemical Company, Freeport, TX; Core R&D, The Dow Chemical Company, Freeport, TX and Scott J. Bury, Engineering & Process Sciences R&D, The Dow Chemical Company, Midland, MI

Freeport Marine Terminal Operations (FMTO) is a market segment of Dow’s global supply chain, and is the conduit for various Dow businesses in receiving raw materials, and shipping out products to customers via ships and barges from Texas Operations. The terminal operation’s dock assets are configured and have ancillary resources for servicing vessel traffic based on current needs of the businesses at the specified lean asset utilization.  As a result, when new and significant business changes occur, the terminal needs to be re-evaluated for its ability to handle business demands whether through re-configuration, or a larger expansion of resources (e.g., including new dock assets).

The evaluation of terminal capability can be aided by a model that simulates the marine terminal activities and calculates performance metrics. In this talk, we present a discrete event simulation model that we have developed to aid in the assessment of terminal capability. We realistically model marine terminal operations by capturing all the steps involved in marine terminal operations – the timings of which are defined using distributions developed from historical marine terminal data. In addition, subject matter experts are consulted to ensure that the decision-making criteria of the model closely mirror actual decisions.

We then present our decision-making methodology on several test cases. In doing so, we demonstrate our tool’s ability to quantitatively assess marine terminal capability while incorporating the uncertainties associated with terminal operations and variability in vessel arrival and movement times; additionally, we implement statistical tools to accurately depict terminal performance beyond using just the mean and standard deviation. Finally, we facilitate decision-making by distilling simulation results into meaningful interpretation: this is a key step in which statistical knowledge is applied to interpret the model results within the context of the decisions being made.

Extended Abstract: File Not Uploaded
See more of this Session: Decision-Making for Industrial Process Systems I
See more of this Group/Topical: Computing and Systems Technology Division