Abstract

The container tracking data is crucial for the effective management of supply chains. In

this report, we analyze container tracking data to identify areas for improvement in supply chain operations. Our study aims to provide insights into the factors affecting container movements,

identify areas where delays and bottlenecks occur, and suggest ways to optimize operations. The supply chain is a complex system involving multiple parties, including shippers,

freight forwarders, carriers, ports, and customs agencies. The timely delivery of goods is critical for maintaining customer satisfaction and reducing costs. Therefore, it is essential to have a robust tracking system that enables the monitoring of container movements and identification of any issues that may arise.

To achieve these objectives, we used the CRISP-DM (Cross-Industry Standard Process for Data Mining) process, a widely used framework for data analysis. The CRISP-DM process involves six phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment. We used this framework to analyze container tracking data and

identify opportunities for improving supply chain operations.

Publication Date

5-16-2023

Document Type

Master's Project

Student Type

Graduate

Degree Name

Professional Studies (MS)

Department, Program, or Center

Graduate Programs & Research (Dubai)

Advisor

Sanjay Modak

Advisor/Committee Member

Ehsan Warriach

Campus

RIT Dubai

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