New Product METIS first with predictive Poseidon Principles Emissions INDEX
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작성자 최고관리자 댓글 0건 조회 1,612회 작성일 21-04-15 14:03본문
METIS Cyberspace Technology has refined its cloud-based data acquisition and ship performance reporting solution to offer shipping’s first tool to predict the trade-off between emissions reduction and debt servicing for ships financed under the Poseidon Principles.
Designed to incentivise maritime de-carbonisation, the Poseidon Principles offer a framework for financial institutions to lend in line with International Maritime Organization goals to halve greenhouse gas emissions by 2050. 20 institutions have signed up, representing over US$150 billion in loans – more than a third of shipping’s global financing. Assessing whether ships merit further investment to keep pace with the IMO average efficiency ratio(AER) underpinning the Principles will be key but, to date, exact emissions targets have not been forthcoming.
Serafeim Katsikas, Chief Technical Officer, METIS says the data analytics specialist has nonetheless created the first viable methodology allowing owners to predict whether their ships would benefit most from investment, a change in operating profile or disposal in response to advancing emissions rules. The unique METIS Poseidon Principles Emissions INDEX could even help owners outperforming AER seek to lower borrowing costs.
If the output is straightforward, the solution’s algorithms draw on hundreds and even thousands of data points, depending on the vessel, while artificial intelligence and machine learning support a ship-specific METIS Poseidon Principles Index sensitive to the realities of operations. Today, over 250 ships use the METIS cloud platform, which combines automated data acquisition with high-grade analysis for fleet managers, chartering departments and ship personnel.
An owner facing suboptimal AER can also use the METIS Index to identify the impact of different shortcomings on ship performance, Katsikas says. In its next phase METIS would add its widely used scenario-based analysis to predict the impact of individual technology upgrades.
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