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Can AI improve equipment maintenance at sea?

Evan Palmejar by Evan Palmejar
8 months ago
Reading Time: 4 mins read
Can AI improve equipment maintenance at sea?

As predictive maintenance and condition monitoring systems are becoming more available, AI is one of the key technologies that is playing a role in the burgeoning growth of the market. In part two of our four article series on AI technologies in the maritime industry, we take a look at how digital twins can be paired with digital health management solutions to give decision makers better visibility of their assets. 

Digital health management, also known as machinery health management, can be described as the combination of technical support services and technology being enabled by digital solutions and data centric processes. It utilises technologies such as computing platforms and smart sensors to ensure that the machinery and equipment onboard the vessel are in good condition and are operating efficiently. 

Digital health management focuses on ensuring the reliability of the ship’s machinery and equipment through the use of diagnostic, predictive, and/or condition-based maintenance approaches. Digital health management is applied in many areas of the shipping industry that can aid technical and commercial teams in making operational decisions that can effectively impact the bottom line of the organisation. Several applications can be observed in anomaly detection, fault detection, diagnostic maintenance, predictive maintenance, and asset utility optimisation. 

More organisations are now placing importance on the value of operational visibility in the global supply chain. Digital health management offers itself as an effective solution by allowing a wide range of individuals within the organisation, such as the executive-level decision makers to the ship operators, to have a better perspective of the technical conditions that the various nodes in the network, such as ships and ports, are experiencing. The introduction of artificial intelligence and the improvements made in the state of Internet connectivity onboard ships has enabled companies like Furuno Hellas SA, a subsidiary of the Japanese marine electronics manufacturer Furuno, to promote the digital transformation of marine maintenance services within the industry.

“…utilise digital twin technology to relay real-time information gathered from the ship’s bridge equipment to help in the identification, diagnosis and rectification of the problems.”

The company has developed HermAce, a digital health management system that aims to provide remote technical support and troubleshooting of the ship’s navigation and communication equipment. The system was designed to remotely monitor, maintain, and test the ship’s equipment. This approach makes the maintenance of navigation and communication equipment more cost effective and predictable by reducing the friction between the actions required and processes involved in having an expert be physically situated onboard the ship. The HermAce system gathers data from various equipment and machinery, and automatically analyses this data using their proprietary model and algorithms developed by the team at Furuno Hellas. They designed the system to utilise digital twin technology to relay real-time information gathered from the ship’s bridge equipment to help in the identification, diagnosis and rectification of the problems. This digital twin creates a virtual copy of the bridge to allow Furuno’s maintenance experts to accomplish their repair and assessment services without physically being present onboard. The system is also supported by a digital maintenance service that is scheduled to occur at a specific frequency to ensure the reliability of the equipment being monitored. 

This system has led Furuno Hellas to be recognised by Lloyd’s Register (LR) for its Digital Twin Ready certification. This certification means that the HermAce system has passed LR’s evaluation process which involved a review of the systems’ engineering life cycle processes, the workflow involved in the model, the development of its algorithm, the conformity of its software, and its information security practices.

Download the full report here

ARTIFICIAL INTELLIGENCE SERIES

In collaboration with Lloyd’s Register, Thetius is delighted to present THE LEARNING CURVE, a report on the state of artificial intelligence in the maritime industry. Read by thousands of industry professionals across the globe, this report examines how Artificial Intelligence (AI) can allow maritime companies across the maritime asset value chain to not only get ahead of the market but accelerate their digital transformation and meet the challenges of the upcoming energy transition.

Over the coming weeks, we will be sharing a series of articles on Artificial Intelligence (AI) as a technology that will guide industry stakeholders in meeting the challenges of the evolving landscape of the maritime industry. Each article will look at an emerging form of artificial intelligence, discuss the opportunities that it can bring to improve an organisation’s competitive advantage, and present examples of innovative startups building upon this emerging technology. 

Download your copy for free @ THE LEARNING CURVE

Evan Palmejar

Evan Palmejar

Evan Palmejar is a Technology Analyst at Thetius and a marine engineer who has sailed onboard oil and chemical tankers. Evan holds a Bachelor’s degree in Marine Engineering and a Master’s degree in Maritime Management. In his free time, Evan likes to fix messy data, build dashboards, and work on his coding skills.

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