Digital Twins for engine condition monitoring and wear prediction by Niels Gorm Malý Rytter, University of Southern Denmark
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In the offshore energy industry, major vendors of wind turbines like Siemens and Vestas have service contracts with their clients and carry out remote condition-based monitoring (CBM), diagnostics and predictive maintenance (PdM) for +10.000 wind turbines using real-time sensor data, weather data, digitalized maintenance, repair records and AI algorithms on component level.
The maritime industry has, despite increasing investments in technologies as Internet of Things (IOT), Real time Connectivity and Artificial Intelligence (AI), been surprisingly slow in realizing a similar set of digital service models on the vendor side and implementing practices for CBM and PdM among ship owners.
The objective of the task is to investigate if and how it is possible to develop CBM and PdM digital twin models for systems and critical components of marine combustion engines which eventually can be integrated into IT applications and embedded in daily onboard and remote work practices of DK shipping companies and partnering equipment vendor(s). The project contributes to the bring the DK maritime industry on the forefront on the area of digitalisation and sustainable ship operations.
From the meeting: ShippingLab – setting sail on a new large collaboration project
ShippingLab is initating a new large project focusing on developing technologies on advanced ship design, biofouling, remote navigation, predictive maintenance and the well-being of seafarers.
The leading partners in the project will present their activities, and ShippingLab will talk about the different possibilities to be part of the many activities performed to develop and support Blue Denmark.
It is the Government’s stated ambition to maintain and expand Blue Denmark's position as a growth engine in the Danish economy. ShippingLab implements this ambition, having stakeholders across the maritime industry joining efforts on pre-competitive initiatives.
In a new, large ShippingLab collaboration project starting on May 1, 2024, the partners work together on increasing energy efficiency, accelerating the green transition of the global maritime sector, and developing the position of Blue Denmark as frontrunner for decarbonization and energy-efficiency.
The project sets three key goals that will increase job and value creation compared to 2020
• Reduce CO2 emissions of the Danish fleet by 25% by 2030
• Increase the turnover by 30% by 2030
• Attract 40% more students to maritime MSc programmes
With the launch of SLGREEN at the ShippingLab platform, the Danish maritime community initiates ambitious maritime research, development, and innovation. Building on valuable experiences starting in 2015 with Blue INNOship and the ShippingLab platform initiated in 2019. The wide range of partners – from established, large corporations to new, emerging businesses, universities and maritime university colleges, GTS institutes, organizations, and public authorities etc. – ensures a valuable maritime collaboration on research, development, testing and validation of innovative solutions that supports the common goal of SLGREEN. Further, the presence of some of the largest ship owners within the different segments underlines and value derived from the activities from SLGREEN.
The technological objectives of SLGREEN meets the overarching objective and responds to the global challenge by developing up to TRL7 an array of digital technologies that contribute to the goals:
• Objective 1: Develop vessel performance prediction tools to improve navigation in waves
• Success Criterion: A digital twin for vessel performance in waves tested on commercial routes
• Objective 2: Develop biofouling prediction models for managing hull performance
• Success Criterion: A biofouling prediction model is integrated into the vessel performance system of partner ship owners
• Objective 3: Condition monitoring and wear prediction model for marine combustion engines
• Success Criterion: A digital twin for predicting wear is integrated into the engine performance monitoring system of partner engine-maker
• Objective 4: Develop an integrated system for digital pilotage enabling remote navigation
• Success Criterion: The digital pilotage system is validated through full-scale demonstrators
• Objective 5: Develop a system for improving the comfort and health of crew on board
• Success Criterion: A digital pilot demonstration and guidelines on mitigation technologies
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