Rapid technological advances are likely to grow the footprint of digital twins in ship design and operations, including for dealing with emergencies and other safety-related issues. The shipping industry’s green drive is fuelling this development.
By Kari Reinikainen
A digital twin is a virtual replica of a vessel and its systems. It uses real-time data from sensors to simulate, monitor, and optimise the ship’s operation and management profiles. By combining AI, internet of things, and software analytics, it enables predictive maintenance, simulation, and improved decision-making throughout the vessel’s life cycle. A digital twin is thus an effective tool for the maritime industry in multiple ways.
Improving design decisions
According to Naoki Mizutani, managing director of NAPA Japan, the green transition of shipping requires significant focus on innovation, and digital twins could play a major role in this. In late 2023, he said that more efficient design would be needed in the maritime industry, with streamlined collaboration among different stakeholders. Simulation tools that provided greater accuracy and certainty about the impact of design decisions were another key requirement.
Digital technology helps naval architects to test different design parameters from the earliest stages. “For example, they can assess various configurations, fuels, and propulsion systems, depending on the vessel’s future route, and evaluate where new systems such as batteries or additional fuel tanks could be installed on the ship,” Mizutani said. “By providing this additional clarity and granularity, we can better understand the different fuel options and their implications at sea, even before any steel has been purchased.”
When it comes to retrofits, digital twins, which contain data on a vessel, can help calculate the impact of installing new technologies, such as scrubbers, batteries, carbon-capture systems, and new tanks. “They enable [design] teams to test the effect of added weight on a vessel’s configuration, cargo capacity, stability, and performance at sea,” Mizutani said.
The benefits of a digital twin carry on throughout the life cycle of a vessel. “A ship’s digital twin has the potential to help maximise operational performance, optimise fleet operations and efficiency per ton-mile, minimise total fleet emissions and costs, better plan maintenance schedules, and ensure compliance with regulations such as Carbon Intensity Indicator,” said Mizutani. “Data from a vessel’s digital twin can indicate that by switching to methanol, for example, a ship’s operations may need to also consider revising its bunkering schedule to accommodate more frequent replenishment of water. This gives owners and operators the peace of mind that they are operating as safely and efficiently as possible.”
Mizutani emphasised that, as more vessel and voyage data became available, shipyards could continue to refine their 3D models and simulations to better understand the impact of their design decisions and make better informed choices.
But achieving this, according to Mizutani, would also require data sharing and cross-industry collaboration among shipowners, shipyards, operators, and technology providers to enable development solutions that would benefit the entire industry’s green transition.
Classifying and certifying
Digital twins are useful for classification societies, too, and this certainly applies to cruise vessels because of their complexity. “Cruise ships are among the largest, most complex vessels in operation – essentially floating cities with tightly integrated propulsion, power, hotel, safety, and guest-service systems. Digital twins can give classification societies a powerful way to better understand how those systems behave over time, not just at a single survey date,” said Eric VanDerHorn, technology director at American Bureau of Shipping (ABS).
A digital twin, properly calibrated with real operational data, can help simulate future asset behaviour, predict degradation, and support decisions on inspection timing, repair strategies, and life extension. For classification societies, the discussion is shifting from whether the data is available to whether the data is qualified and trusted enough to support safety‑critical decisions.
“Digital twins support a condition‑based approach to classification society by providing a continuously updated view of hull and machinery health,” said VanDerHorn. “This enables more targeted, risk‑based surveys that can help minimise disruption to itineraries and dry-dock schedules. Experience from offshore and other sectors shows that combining digital twins with disciplined condition monitoring and alarm management can help reduce unplanned downtime and improve operator clarity.”
Companies and organisations in this field, such as ABS, have established useful frameworks and guides to evaluate and certify digital twin technologies. “They help ensure that digital twins used for classification decisions are based on trusted data, governed like safety‑critical systems, and capable of generating reliable information that both the classification society and cruise operators can depend on,” VanDerHorn told CruiseTimes.
Embedding AI
AI is already being embedded in digital twins across marine and offshore industries, and that trend is accelerating in the cruise sector. “In many cases, digital twins today use physics-based and analytical models that are refined with vessel-specific operational data,” VanDerHorn said. “AI and machine learning [ML] are increasingly used to enhance those models, improve anomaly detection, forecast degradation, and suggest optimal operating points.”
For some applications, such as structural load and fatigue assessment, well-established engineering models will remain central, with AI simply helping to detect patterns or data quality issues. “For others, such as machinery health monitoring, hotel load optimisation, and HVAC performance, AI and ML can add more significant value by learning from large volumes of operating data across voyages, seasons, and ship configurations to help detect deviations from normal operations,” VanDerHorn said. “In the cruise context, AI-enabled digital twins can help operators explore ‘What if’ scenarios across propulsion, power, and hotel loads, while balancing fuel consumption, emissions, comfort, and risk.”
They can also support condition-based maintenance by turning continuous data streams into clearer, more bounded recommendations for crew. “The direction of travel is not AI replacing human judgement, but AI-enabled digital twins carrying more of the data and analysis burden, so that crews and classification societies can focus on high-consequence decisions,” VanDerHorn said.
In this way, AI would change the role of digital twins from being primarily engineering and reporting tools to becoming real‑time decision‑support systems. “In the near term, the biggest impact is on how quickly and confidently crews and surveyors can interpret complex data,” he said. “AI can help digital twins prioritise and contextualise alarms, so that crews can focus on the most critical issues rather than being overwhelmed by noise. It can detect subtle patterns in machinery performance or structural responses that might precede failures or service disruptions. It can also run scenario simulations in seconds, quantifying trade-offs between route choices, speed profiles, environmental conditions, guest‑comfort parameters, and maintenance risk.”
Broadening application
Further into the future, as trust in these AI‑enabled systems grows, and as verification and validation frameworks mature, digital twins may be able to take on more operationally critical roles – always within clearly defined, bounded authority. “For example, a digital twin might recommend adjusted set‑points for propulsion or HVAC to stay within emissions targets while preserving comfort and schedule reliability, with the crew retaining final control,” VanDerHorn said.
For classification, AI‑enabled digital twins can support a gradual evolution from periodic, paper‑based assessments to more continuous, data‑driven insight. The key is that AI is embedded within a robust governance framework, verification, validation, cybersecurity, and clear human‑in‑the‑loop procedures, so that it can enhance safety and integrity rather than simply adding complexity.
Most of the early adoption of digital twins for preventive and condition-based maintenance has focused on propulsion and critical machinery. Here, digital twins have helped enable a shift from fixed, calendar-based interventions to condition-based maintenance informed by actual operating data. “We’ve seen capabilities evolve from simple anomaly detection to more advanced diagnostics and prognostics, predicting when failures are likely to occur in the future,” VanDerHorn said.
Experience from offshore oil and gas and the wider energy sectors is instructive. There, digital twins – combined with disciplined condition monitoring and alarm management – have reduced unplanned downtime and improved clarity in high-stakes operations.
Applied to cruise ships, the same principles can support:
- more targeted surveys and inspections, by focusing effort where risk is highest rather than dismantling healthy equipment
- improved itinerary reliability, by identifying emerging issues early and planning maintenance around voyages and dry-dock windows.
- better alignment between maintenance and guest experience, for example, by using machinery and HVAC twins to help avoid failures that could disrupt comfort or onboard services.
“Preventative maintenance programmes are already being used to help inform class surveys and, where justified, avoid intrusive inspections on equipment shown to be in good health,” said VanDerHorn. “The general pattern is that data-led, digital-twin-informed maintenance programmes can improve availability and reduce surprises, but it requires disciplined data quality, clear operating procedures, and collaboration between operators, OEMs, and classification societies.”
Updates essential
Keeping a digital twin up to date is essential to its credibility, and cruise ships face some specific challenges. The harsh marine environment can degrade sensors and communications equipment, and connectivity at sea is still not as robust as on shore.
“Digital twins that rely heavily on cloud-based processing are particularly sensitive to data outages. These systems typically buffer and retransmit data when connectivity is restored, but where uninterrupted insight is required, more processing is moving on board,” said VanDerHorn. “There are also practical issues around change management: every modification, equipment replacement, or software update needs to be reflected in the digital twin, data model, and configuration records. If this doesn’t happen consistently, the digital twin can diverge from reality and lose authority.”
The consequences of gaps in the update of a digital twin depend on how the twin is being used. “For advisory applications, such as performance benchmarking or planning future maintenance, gaps or delays in updating the twin primarily may reduce the quality and usefulness of insights,” VanDerHorn said. “For operationally critical applications, such as decisions that directly affect safety or compliance, misalignment between the twin and the actual vessel may be unacceptable.”
VanDerHorn stressed that, as digital twins become more central to operations and classification, the industry would adopt risk-informed frameworks, verification, and validation practices to manage risks. “That includes defining clear data ownership, governance processes to ensure that changes on board are reflected in the model and safeguards and fallback modes if data quality or connectivity falls below acceptable thresholds,” he said. “Many maritime digital twins today are intentionally deployed in a way that complements existing processes rather than replacing them outright, so that a loss of digital capability does not compromise safe operation.”
Digital co-pilot
Today, many digital twins in the cruise sector are highly focused tools: they might cover a specific engine, a critical drive system, or a narrow set of performance metrics such as fuel efficiency or emissions. ABS expects that by 2030, digital twins will become more integrated, more predictive, and more embedded in everyday decision-making.
“On the newbuilding side, ships will increasingly be designed as digital-first assets,” VanDerHorn said. “That means specifying sensors, data models, and connectivity with digital-twin-use cases in mind, from energy optimisation and structural integrity to hotel systems and guest experience. Rather than building a ship and then creating a digital representation, the industry will move toward developing a robust digital model early and using it to guide design, construction, commissioning, and operations. On board, separate twins for propulsion, power, HVAC, hotel loads, safety systems and structure will be more tightly connected, providing a unified operational picture of the ship.
“This will allow operators to better simulate full vessel scenarios: how a routing decision, weather pattern, or itinerary change affects fuel, emissions, comfort, and asset health together.”
For crews, the experience of using a digital twin will feel less like using a specialised engineering tool and more like working with a digital co-pilot: a system that can help synthesise complex, cross-domain data into clear guidance, while leaving final authority with the people on board.
As ships become larger and the crew leaner, these capabilities may be essential to operating cruise fleets safely, efficiently, and sustainably.
Consolidating systems
“Maritime operations involve highly interconnected systems, distributed data sources, and complex, often time-critical decisions, said Dr Gerald Däuble, head of LHIND Digital Twin at Lufthansa Industry Solutions, an IT consulting and system integration company that is part of the Lufthansa group.
The company has more than two decades of experience in maritime projects, supporting cruise lines, shipyards, and operators worldwide in building resilient digital capabilities and modern operating models.
Its maritime portfolio combines highly available IT infrastructures with advanced digital solutions tailored to ship operations. “We enhance these foundations with AI applications to improve efficiency, transparency, and operational safety, all aligned with practical onboard realities,” Däuble told CruiseTimes.
The LHIND digital twin enables transparency, cross-system coordination, and data-driven decision-making in complex ship environments – especially for crew who are not data scientists.
It consolidates data from multiple sources (systems, processes, sensors) into a single interactive platform. The company also offers guest-facing and optimisation solutions, such as digital boarding for faster check-in, efficient cabin management, guest-flow management in high-traffic zones, and AI-supported reduction of food waste. In each case, the digital twin turns operational complexity into actionable clarity.
Together with HIKvision and EW Production Services, LHIND has developed a man-overboard detection feature that is integrated in its digital twin. The system uses thermal and conventional imaging in fixed cameras and mobile binoculars, plus AI-based computer vision. These systems are combined and synchronised to create a clear, role-specific visualisation for everyone during such an emergency.
“Only by connecting all systems into a single smart solution do we create a reliable real-time operational picture, the foundation for fast, informed decision-making. This innovation emerged from collaborative ideas, integrated ecosystems rather than individual technologies,” Däuble said.
Compatibility vital
As with all computer-based systems, it is important that the software used in a digital twin works with all the relevant stakeholders.
But this was not always the case. In 2025, media reports started to circulate about a major German naval shipbuilding project running into unexpected difficulties. It involved a series of six 10,550-tonne displacement frigates of a new class, called the F-126. The Damen group was in charge of the design, and the ships were to be built in Germany by Blohm + Voss and Peene-Werft.
On 13 February 2026, a report emerged in Defense and Security Monitor that said: “IT interfaces used in the design and manufacturing system reportedly had significant technical problems, slowing the process down considerably. To make matters worse, Damen ran into problems transferring vital construction plans and information to German partners, a problem that was only declared resolved in January 2026. The resulting backlogs have delayed the project at least three years, with some German lawmakers complaining that the Navy could not offer a firm operational date for the first ship.”
Although this is precisely the kind of costly scenario the cruise industry ought to avoid, it should in no way overshadow the efficacy of digital twins in ship design and operation, or dampen the enthusiasm for developing and adopting the technology for the sector, because it offers exciting opportunities.