Enhancing Port Efficiency and Lead Time Reduction through Predictive Analysis: A Case Study of Container Management at Khalifa bin Salman Port

Author

Abdulaziz A. Aljalahma

Date of Award

3-2024

Document Type

Thesis

Degree Name

Master of Science in Logistics and Supply Chain Management

Department

Department of Operational Sciences

First Advisor

William A. Cunningham III, PhD

Abstract

Khalifa bin Salman Port (KBSP), a key pillar in Bahrain's maritime infrastructure, is the focal point of this study, highlighting the significant role of predictive analytics in optimizing port operations. This thesis analyzes container throughput data from 2017 to 2022, provided by Bahrain's Ministry of Transportation database. This data forms the basis for forecasting the 2023 throughput. The study thoroughly compares these predictions with the actual 2023 data, assessing the predictive model's accuracy. The findings underscore the importance of predictive analytics in strategic decision-making for port management, focusing on enhancing operational efficiency and reducing lead times. This research offers a comprehensive guide for port congestion at Khalifa bin Salman Port.

AFIT Designator

AFIT-ENS-MS-24-M-062

Comments

A 12-month embargo was observed for posting this work on AFIT Scholar.

Distribution Statement A, Approved for Public Release. PA case number on file.

Recommended Citation

Aljalahma, Abdulaziz A., "Enhancing Port Efficiency and Lead Time Reduction through Predictive Analysis: A Case Study of Container Management at Khalifa bin Salman Port" (2024). Theses and Dissertations. 7701.
https://scholar.afit.edu/etd/7701