of offshore wind turbines in the north sea
The shipping company Ziton services offshore wind farms with a fleet of specially built ships. One of the primary tasks is replacing components such as gearboxes, generators and blades, and this requires a substantial setup process when it takes place on the high seas.
Ziton has a vision of providing the best service for its customers, and thanks to the combination of machine learning and several years’ experience on the water this is now an option, as the combination provides them with a unique opportunity to give its customers a qualified offer regarding the need for maintenance, and to identify any error rates.
Predicting future tasks
AI and machine learning enable Ziton to predict future tasks. Ziton has a strong focus on remaining competitive and keeping a close eye on staffing, fuel consumption and costs in the form of port calls. Through machine learning and predictive maintenance Ziton’s ambition is to be able to make optimum use of both material and human resources.
Optimum use of resources
Ziton now collects its data in one place, and on the basis of this data, machine learning helps them see future trends. They can now adapt their resources as needed, and be at the forefront of investment in specially adapted vessels, making it easier for them to meet the requirements of future turbine types.
insight into data
creates the ability
to take action
The industry in which Ziton operates is characterised by very large capital investments on which interest must be paid for many years, thus prediction of future business potential is of huge importance to future earnings. This prediction can also give Ziton a basis for taking action, as they now act on their collected data and histories, thereby reducing uncertainty.
“Our business is totally dependent on error rates on offshore wind turbines in the North Sea. We make very big investments on the basis of our expectations for the future. They used to be based on gut feeling, but we now use algorithms to predict error rates on future offshore wind turbines.”
Jens Michael Haurum, CFO, Ziton A/S
from a technical standpoint
Ziton’s benefit from the project is mainly thanks to a combination of the latest technology and industry experience within the business. The solution is based on Microsoft’s Azure Machine Learning platform.
The data used comes from a number of internal and external sources, which are combined to create the optimum prediction. It is a single platform of which machine learning is an integral component. The entire flow is automatic, and forms an integral component of their data warehouse. In other words it all now runs by itself, and Ziton can quickly and easily extract correct information, predict tendencies and act on them.
book a non-committal
meeting or call
Thank you for visiting inspari.com. Please do not hesitate to contact us, if we may be of any help to you. Just send us your contact information in the form to your right, and we will call you back as soon as possible.