Greece-based Propulsion Analytics, a provider of vessel and engine performance evaluation applications, and DNV have obtained funding from Innovation Norway for the development of a condition-based maintenance (CBM) application for vessels.
The new CBM application will use authenticated methods and accredited tools and combine thermodynamic modelling with artificial intelligence (AI) to forecast performance in marine powerplants and detect faults in machinery systems
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As part of the project, Propulsion Analytics will also upgrade its analysis method and tools to manage the functioning of marine engines.
The analysis method will integrate physics-based process simulation models and data-driven models powered by AI.
It will be able to create a reference performance for a powerplant’s working condition, which will be compared to actual data to help identify and predict engine component malfunctions or declining performances.
Propulsion Analytics general manager Efstratios Tzanos said: “Currently, less than 2% of the world’s fleet employ a CBM arrangement, but in the next 10 years we expect that 10% of the world’s fleet will use performance optimisation tools and CBM methods.
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By GlobalData“Ship performance evaluation, incorporating efficiency optimisation and improved maintenance scheduling can result in significant cost reductions for ship owners and operators. At Propulsion Analytics we are using cutting-edge technology to develop an innovative CBM application and CBM service to meet these needs.”
To evaluate the CBM application, DNV will develop a verification, validation, and accreditation (VV&A) methodology, which is expected to improve the legitimacy and reliability of CBM approaches.
DNV South-East Europe, Middle East and Africa R&D and advisory head George Dimopoulos said: “CBM holds the promise of safer, more reliable and competitive operation of maritime assets. In this project we are aiming straight for the heart of seagoing vessels, the marine engine. DNV will develop digital validation and verification methodologies to build confidence in the use of CBM for critical equipment and hopefully accelerate their deployment in shipping.”
