Benchmarking Dry Bulk Terminal Unloading Performance Using Open Data and OEE Analysis

Abstract

Dry bulk terminals play a key role in global supply chains, yet a comparative analysis of their operational performance is difficult to evaluate due to limited data access and inconsistent reporting. This study introduces a scalable method to assess unloading performance using open data sources, including Automatic Identification System (AIS) vessel tracking, aerial imagery, and publicly available equipment information. Terminal activities are translated into measurable indicators and analysed through an adapted Overall Equipment Effectiveness (OEE) framework capturing crane utilization, crane productivity, and berth commitment. A discrete time model reconstructs operational states for each
vessel call using standardized assumptions for downtime, maintenance, and pre and post operational procedures.
Validation with operator data from terminals in Rotterdam and IJmuiden shows that cargo throughput, quay occupancy, and crane utilization can be estimated with reasonable accuracy using open data alone. Applying the method to four Northwestern European terminals reveals OEE values between 21% and 36%, with notable variation in utilization and productivity.
Benchmarking highlights differences driven by operational choices as well as external factors such as transit conditions and cargo mix. The results demonstrate that open data offers sufficient resolution for comparative analysis, early-stage design validation, and benchmarking. Despite remaining uncertainties in internal logistics, the methodology provides a cost effective and replicable framework for assessing dry bulk unloading performance with opportunities to expand to dry bulk terminal level.