AkzoNobel announced the launch of Intertrac Vision Lite, a free version app of its big data hull performance prediction tool. The app helps ship owners and operators in the hull coating selection process, as well as to explore the role of big data in supporting hull performance predictions.
In May 2017 at Nor Shipping, the company launched ‘Digital Voyage’, a suite of digital tools which included Intertrac Perform, a tool that measures and monitors hull performance data, and validates these against the predictions made by Intertrac Vision, using metrics that comply with the ISO 19030 standard on hull and propeller performance monitoring.
Part of Digital Voyage, Intertrac Vision Lite has been developed to showcase key features of the full Intertrac Vision tool. Users can input data covering a sample selection of vessel types, fouling routes and generic hull coating choices to create different coatings scenarios, and then compare variations in the effect on power requirements, fuel costs, and CO2 emissions. It also includes tips and commentary to explain the methodology that underpins Intertrac Vision, which includes the full range of parameters, and can be used to make comprehensive economic and environmental decisions.
Robert Wong, Marketing Director at AkzoNobel Marine Coatings, said that this development reflects the company’s vision to show the value that big data can bring to ship owners’ decision-making processes.
“This version gives users a very clear idea of what they could learn in a consultation with an Intertrac Vision consultant, using the full version to explore scenarios encompassing a large number of variables, such as different vessel types, operating profiles, fouling challenges and coating options”, he explained.
Launched in 2015, Intertrac Vision is a digital consultancy service for ship owners developed over a four-year period. It combines data on the fouling challenges of different trading routes data with hydrodynamic analysis to predict hull performance. The software uses 3.5 billion data points, incorporating hundreds of thousands of datasets to ensure the highest degree of accuracy.