Including greenhouse gas emissions in a shipping company's decision making for the logistics of spare parts

A case study for chemical tankers

Master thesis (2023)

Authors

B. Rossewij Mechanical Engineering

Contributors

J.F.J. Pruyn Ship Design, Production and Operations - Mechanical, Maritime and Materials Engineering (supervisor 1)
B. Atasoy Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering (supervisor 2)
Faculty
Mechanical Engineering
Copyright: © 2023 Bas Rossewij
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Published Date

24-11-2023

Language

English

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Faculty

Mechanical Engineering

Abstract

Shipping companies aim to reach the climate goals by following the rules from the International Maritime Oranization (IMO), which includes reducing Scope 3 emissions. Maintenance is a great contributor to the Scope 3 emissions of a shipping company, especially the transportation of spare parts. The current state-of-the-art supply chain optimisation for spare parts is based on cost and risks. This study aims to find the potential influence of including Greenhouse Gas (GHG) emissions into the decision-making process for the logistics of spare parts. The element of the supply chain that makes it possible to plan when a spare part is needed is the maintenance policy. Planning in advance when a part is needed is possible for Preventive Maintenance (PM), which is therefore used in this research. A model can be created by limiting the amount of risk, optimising between the freight cost, the cost of GHG emissions and the cost of capital for alternative delivery locations, using brute force calculations. This model is applied to a case study of a chemical tanker from Stolt Tankers B.V., using available data on its job history and historical location data. From the case study follows that including the GHG emissions in the decision-making process adds an additional saving in emissions and cost with respect to the original situation. It can be concluded that the amount that is saved depends on the choices of the decision-maker. The model presented in this paper is a valuable tool for providing insights into the decision.