What is the Challenge that is being addressed?

In addition to the execution of the complex maintenance tasks, the scheduling and planning tasks that need to be performed by a wind turbine maintenance service provider are a challenging and value-adding responsibility. Once a plan has been established it must be constantly revised due to short-term changes in available resources such as ill employees, equipment outages or sudden incoming service tasks that need immediate attention. With hundreds of national and international service points and a multitude of employees spread over multiple teams, the complexity of these tasks requires multiple employees with expert knowledge to adequately assign service teams to service orders. Automating this task opens up new possibilities by cutting down planning times, improving plan quality and making the planning process independent of individuals. This is even more important considering that XERVON is growing rapidly which further increases planning complexity. The improvement in planning can also benefit different aspects of XERVON´s business activity like minimizing overall operating cost, reducing the ecological footprint, reducing working and travel time by the personal as well as reducing wind turbine downtime.

What is the AI solution the project plans to implement?

The most important decision to be made in the servicing of wind turbines is scheduling the numerous service teams to different service orders. For this reason, we aimed to assist the human planners in this task by creating a digital planning board in which orders can be scheduled either manually or automatically using the UPF. The problem was solved by modelling it as a vehicle routing problem considering travel and work durations with constraints regarding the total amount of time available for each team within the UPF.