What is Vessel Performance Analysis?
Ships have plied international waters since ancient times. Before the advent of aviation, ships were the primary means of transportation for trade across oceans or continents.
Today, 90% of global trade relies on maritime transport. While economic activity in other parts of the world stalled during the pandemic, cargo ships continued to operate.
With the rapid growth of the population and its synchronization with global markets, maritime transport volumes fluctuate from time to time. The oceans are more crowded than ever, but thanks to innovation and advanced technology, sea routes connect to nearly every corner of the world. Modern ships are designed to withstand harsh conditions, including inclement weather and rough seas.
Maritime Transportation
The technological revolution has had a significant impact on the shipping industry in areas such as computing, automation, connectivity, and digitalization. Today, sailors no longer need a compass as large as a clock to track their course. Everything can be precisely monitored on a small computer screen.
Thanks to automation, advanced systems can control many aspects of a ship’s navigation, including maneuvering and maintaining course. If the Titanic had sailed today, disaster could have been avoided thanks to precise detection and sensors that could alert control centers to obstacles from meters away. Fuel consumption was also continuously monitored.
Now, let’s look at vessel performance analysis, another major milestone in the shipping industry, where computing and data management play a key role.
Data Analytics Overview
Before moving on to vessel performance analysis, it’s worth briefly reviewing data analytics.
Data analytics is a branch of data science, the computational science and technology that explores, utilizes, and processes large amounts of data with practical applications.
Data science primarily encompasses the following areas:
- Data Analysis, Visualization, and Engineering
- Machine Learning
- Artificial Intelligence
We won’t delve into the concepts of machine learning and artificial intelligence. However, suffice it to say that these are advanced data science applications that use advanced computational methods to easily solve complex real-world problems.
Data analytics processes large data sets to extract knowledge for a variety of purposes. The first step in data analysis is to visualize, examine, and monitor the data. Then, useful information is extracted from the raw data to gain insights. Data engineering, the final step and a distinct discipline, typically follows data analysis. Other uses of data engineering involve applying programming languages, computer software, and techniques to manage algorithms and leverage existing data sets to achieve the desired objectives.
Vessel Performance Analysis
Any operating vessel is subject to a variety of parameters. This data encompasses everything from fuel consumption and efficiency to voyage time (including layovers and port calls), engine performance, speed, weather conditions, trim and stability information, propulsion data, and hull and propeller condition.
Previously, much of this information was either unrecorded or recorded manually to some extent and stored in logbooks as needed. However, with advances in computing and communications technology, many shipowners and charterers are increasingly interested in closely monitoring all of this detail in real time. The reason is this: Ultimately, all companies and shipowners strive to maximize efficiency without compromising standards to reduce costs (e.g., fuel consumption).
For the same reason, easy access to all relevant vessel data provides a better understanding of the vessel’s overall performance. This allows for a more comprehensive assessment of any deficiencies and ways to improve efficiency. Furthermore, the latest emission regulations have increased the need for vessel performance monitoring to monitor emissions and ensure compliance. Given the increasing incidence of accidents caused by maritime traffic and adverse weather conditions, vessel monitoring is also crucial for maritime safety.
Broadly speaking, the field of vessel performance analysis encompasses the following three areas:
- Vessel Performance Monitoring and Reporting
- Analysis
- Improvement
The first and most important step is vessel performance monitoring. This system is essentially a two-way communication system between the vessel and the operator, owner, or charterer, providing readily available data on vessel performance and operations. The vessel transmits all critical information (such as fuel consumption, engine performance, propulsion data, routes, sailing and call times, port schedules, cargo information, ballast information, and weather reports) to relevant stakeholders.
Data is collected, processed, stored, and used for analysis and feedback. Feedback is then transmitted from ship to ship, and any input related to performance improvements or advisory measures is integrated and returned to the ship. In this way, real-time onboard data can be used to optimize vessel operations. Monitoring can be conducted for a group of vessels or the entire fleet, which is known as fleet performance monitoring.
Vessel Performance Analysis
Analysis occurs immediately after vessel performance monitoring. Processed data from the vessel is analyzed to better understand the vessel’s current condition. Information obtained from the vessel’s data over a specific time period is compiled into a “Vessel Performance Analysis/Assessment Report.”
This information is known as “Key Performance Indicators” (KPIs). These indicators are typically compared to standard or desired KPIs (defined as benchmarks). The difference between the actual achieved performance and the benchmark is carefully evaluated and reported to the vessel for reference.
Any discrepancies or changes are crucial for improving operational procedures. This is known as “vessel performance improvement analysis.” For example, a vessel is in a specified trim and heading for a port of call. However, its fuel efficiency, based on the optimized fuel consumption target, is not meeting expectations. Furthermore, because the engine is running strong and on a fixed schedule, it is not possible to reduce speed. Therefore, in this case, adjusting the ballast water to an appropriate level can help improve fuel efficiency with minimal cost or effort.
Vessel performance improvement analysts evaluate this data and, after final confirmation, use advanced computing technology to transmit it to the vessel. Similarly, suppose that severe weather conditions are likely to occur on a vessel’s chartered route. This could result in increased fuel consumption and voyage delays, jeopardizing the vessel’s safety.
While weather-related information is readily available through the ship’s weather system or other specialized weather reporting agencies, planning alternative routes is crucial. This can also be managed using relevant data on vessel performance, including weather, fuel consumption, and other alternative route details. Therefore, route planning can provide significant benefits from a safety perspective.
Vessel performance optimization and performance management utilize valuable analytical information to continuously improve vessel operations and performance standards. They provide recommendations and guidance for quality control and maximum performance.
As previously mentioned, vessel performance optimization and improvement activities were primarily carried out by charterers, operators, or shipowners. However, due to growing demand, responsibilities are being delegated to various organizations, companies, and even external classification societies. Best practices for vessel performance optimization and improvement depend on available technology and the speed of its implementation. Tour operators or outsourcing agencies invest significant resources and expertise in acquiring and developing advanced software to achieve optimal performance improvements.
Best practices for improving and optimizing vessel performance depend on the availability of technology and the speed of its implementation. Travel companies and third-party suppliers invest significant resources and technical expertise in acquiring and developing advanced software to achieve optimal performance improvements.
The onboard technological infrastructure is equally crucial for ensuring the accurate transmission of information needed for analysis and performance improvement. Data visualization and analysis were previously and still are based on simple tools such as Microsoft tools or languages like Python and Java. However, in recent years, advanced, comprehensive software has become widely available for analysis, reducing the time and effort required.
