Skip to the content.

Integrated Vessel Health Management (IVHM) for the Maritime Autonomous Surface Ship (MASS)

Project ID: 2228cc1457 (You will need this ID for your application)

Research Theme: Engineering

UCL Lead department: Mechanical Engineering

Department Website

Lead Supervisor: Yuanchang Liu

Industry partner: MarRI-UK

Stipend enhancement: £1,000 pa

Project Summary:

Maritime Autonomous Surface Systems (MASS) have the potential to revolutionise the maritime industry by increasing efficiency and reducing operational costs. However, their successful deployment relies heavily on the seamless functioning of various components and systems. To ensure the sustained availability and functionality of MASS, a robust maritime strategy is required. This proposal outlines a project aimed at developing such a strategy through the integration of sensing capabilities, advanced communication systems, and AI algorithms, to achieve enhanced awareness, improved maintenance efficiency and reduced human errors for MASS. Partially funded by MarRI-UK and its industry member, Lloyds’ Register, this DTP-CASE project will provide a strong link with a leading maritime industry, and a unique opportunity to interact with experienced engineers via joint research exploration and validation.

The project will involve the design and implementation of sensors and communication systems on MASS, the development of AI algorithms for data analysis and decision-making, and the establishment of an optimised logistics framework. Field tests and simulations will be conducted to validate the effectiveness of the proposed strategy.

The research is expected to result in a comprehensive maritime strategy for MASS that reduces operational costs, enhances system availability, and minimises the impact of human error. This strategy will contribute to the wider adoption of MASS in the maritime industry, promoting efficiency and sustainability.

By developing critical engineering skills in autonomy and automation, data acquisition, calibration and processing, a next generation autonomous shipping specialist will be trained from this project. Key research skills including analysis & problem-solving, project management & organisation, interpersonal & leadership, written & oral communication, etc. will be trained by the supervision team as well as UCL doctoral school training courses. The project will also be working closely with MarRI-UK and its industry members and industry supervision and internships opportunities will be provided.