Stock modelling

Historical ship data provides a valuable foundation for modeling the stock of ships both in the past and into the future. By analyzing shipbuilding trends, decommissioning rates, and fleet composition over time, we can develop a dynamic representation of the global shipping fleet. This work makes use of the ODYM – Open Dynamic Material Systems Model, which enables a structured approach to modeling stock dynamics, including inflows, outflows, and overall fleet evolution. If you are part of the MariTeam model team, you can access the scripts and methodology used for these calculations in our repository. This resource provides the tools needed to explore historical trends and project future fleet developments under different scenarios.

Historic data

The plot below displays the historic number of ships that have been built in each year, categorized by ship type, including those that have been eventually decommissioned. This dataset provides a comprehensive view of shipbuilding trends over time, showing not only the new ships that entered service each year but also accounting for those that were decommissioned, offering a complete picture of the evolving global fleet.

Lifetimes

The lifetime of different ship types is a critical factor in understanding the dynamics of the global shipping industry, yet there remains significant disagreement regarding the current average lifetimes of various vessel categories. This lack of consensus stems from the complex interplay of factors that influence a ship’s operational lifespan, such as technological advancements, maintenance practices, and regulatory changes. In the plot below, we present the expected lifetimes for different ship types that were built between 1970 and 1990 and were decommissioned prior to 2020.

The values in this dataset can be approximated to follow a normal distribution. To aid in this, we provide the mean (mu) and standard deviation (sigma) values, which are key parameters of the normal distribution. These statistical measures represent the average and the spread of the data, respectively.

Projections

We utilize projections to understand the future trends in shipping based on Kramel et al. (2023). More detailed information about these projections, along with the methodology and underlying assumptions, can be found on the corresponding page SSP Scenarios, where we explore various future scenarios and their implications for global shipping and climate change. A summary of the main scenarios can be seen below.

Inflows and outflows

We can calculate the inflows and outflows of ships in each scenario using the stock model, providing a detailed view of how the global fleet evolves over time. The inflow represents newly built ships entering service, while the outflow accounts for vessels being decommissioned or removed from operation. This allows us to analyze how different future scenarios impact the overall composition and capacity of the fleet. To make the visualization clearer, you can unselect specific ship types in the plot below, helping to declutter the display and focus on particular categories of interest.

Cumulative stock

To assess how the fleet evolves in response to future demand, we calculate the total ship stock required for a given year based on the selected scenarios. This involves balancing the inflows of new ships and the outflows of decommissioned vessels to ensure that the fleet capacity aligns with projected shipping demand. By integrating these calculations with scenario-based projections, we can estimate the number and type of ships needed to meet future transport requirements.

Author: Diogo Kramel
Model: Ship Dynamic Stock Model
Repository: GitHub
Data Version: v1.0.0 | 2025-02-13
Latest Update: March 26, 2025
Contact: diogo.kramel@ntnu.no