Machine learning as an optimisation enabler for ship management companies

Abstract

The strong focus on sustainability from global and local perspectives is affecting the shipping industry, with new regulations coming into force and expectations aiming to create greener ship transportation and operations. This research explores machine learning as a tool for optimisation within ship management companies, which could reduce fuel consumption and lower emissions of greenhouse gasses. Machine learning is a modern technology with powerful capabilities surpassing human capacity in several areas. This research explores if ship management companies take advantage of the available technology, and the research question is to which degree machine learning is applied for optimisation on ships. It also identifies where machine learning may have an application for ship optimisation, and the study investigates how optimisation is utilised on ships today. The research question is explored using a case study methodology with a qualitative approach, interviewing several ship management executives from ship management companies with head offices in Norway. The companies participating in the research were selected from public registries and comprised major ship management companies operating fleets of ships providing services to the offshore oil and gas industry. The study provides insights into the current practices of optimisation on ships and provides knowledge of what influences optimisation at both high and low levels organisationally. The results indicate that machine learning can considerably enhance fuel optimisation and performance, although it has yet to be commonly implemented on ships. The thesis provides valuable insights to ship management companies considering implementing machine learning on their ships and for other parties providing products and services for on-ship applications. The thesis also provides a list of key learnings that may be used as recommendations for ship management companies implementing machine learning or new technology onboard.