Abstract: Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for training a machine-learning model configured to generate a prediction and recommendation output from input data. The system obtains training data including a plurality of training examples, obtains context data, identifies one or more feature variables from the context data, constructs the machine-learning model based at least on the identified feature variables, generates feature variable training data by processing the training data based on the identified feature variables, and performs training and periodic update (if required) of the machine-learning model to generate model parameter data for the machine-learning model based at least on the generated feature variable training data.

Abstract: A platform for a wind turbine, the platform including a lift beam for carrying a load of a transport cabin of a tower lift of the wind turbine is provided. By the lift beam being part of the platform, an easier installation of the platform and the lift beam is possible. Furthermore, less components are needed. Another advantage is that the lift beam is installed at a smaller height of the tower where the tower has a larger diameter compared to a conventional lift beam. This increases the available space for lift cables hanging from the lift beam.

Abstract: A system and method for facilitating predictive maintenance of an equipment is disclosed. The system may include a data capturer, a plurality of edge computing nodes and a cloud computing device. Each edge computing node may include a first processor. The cloud computing device may include a second processor. The first processor may receive the raw input data from the data capturer and may process the raw input data to obtain a representative data. The representative data may include an insight pertaining to a deviation in the at least one variable and a corresponding remedial action to be taken to correct the deviation. The deviation may be related to a deterioration in the condition of the equipment. The respective edge computing node may facilitate a regulation of the deviation by performing an automated actuation based on the corresponding remedial action.

Abstract: A system and method for facilitating predictive maintenance of an equipment is disclosed. The system may include a data capturer, a plurality of edge computing nodes and a cloud computing device. Each edge computing node may include a first processor. The cloud computing device may include a second processor. The first processor may receive the raw input data from the data capturer and may process the raw input data to obtain a representative data. The representative data may include an insight pertaining to a deviation in the at least one variable and a corresponding remedial action to be taken to correct the deviation. The deviation may be related to a deterioration in the condition of the equipment. The respective edge computing node may facilitate a regulation of the deviation by performing an automated actuation based on the corresponding remedial action.

Abstract: Provided is a method for manufacturing a wind turbine, the wind turbine including a high voltage cable configured to connect a generator of the wind turbine with a switch gear of the wind turbine, the method: a) guiding the high voltage cable inside a tower of the wind turbine from an upper part of the tower to a lower part of the tower, and b) returning the high voltage cable at the lower part of the tower up again. Returning the high voltage cable at the lower part of the tower up again simplifies storing an additional length of the high voltage cable inside the tower.

Abstract: Examples for a prospect assessment system are provided. The system may receive a query from a user and obtain prospect data from a plurality of data sources. The system may create a plurality of prospect clusters. The system may determine a cluster significance value. The system may determine a prospect churn value. The system may determine a set of significant prospect clusters from among the plurality of prospect clusters having the cluster significance value and the prospect churn value above a threshold value. The system may determine a prospect pattern matrix including a plurality of patterns from the set of significant prospect clusters. The system may identify a set of products for each of the plurality of patterns. The system may determine a prospect profile for each of the plurality of patterns. The system may generate a prospect assessment result based on the prospect profile for the resolution of the query.

Abstract: Examples for a prospect assessment system are provided. The system may receive a query from a user and obtain prospect data from a plurality of data sources. The system may create a plurality of prospect clusters. The system may determine a cluster significance value. The system may determine a prospect churn value. The system may determine a set of significant prospect clusters from among the plurality of prospect clusters having the cluster significance value and the prospect churn value above a threshold value. The system may determine a prospect pattern matrix including a plurality of patterns from the set of significant prospect clusters. The system may identify a set of products for each of the plurality of patterns. The system may determine a prospect profile for each of the plurality of patterns. The system may generate a prospect assessment result based on the prospect profile for the resolution of the query.

Abstract: A platform for a wind turbine, the platform including a lift beam for carrying a load of a transport cabin of a tower lift of the wind turbine is provided. By the lift beam being part of the platform, an easier installation of the platform and the lift beam is possible. Furthermore, less components are needed. Another advantage is that the lift beam is installed at a smaller height of the tower where the tower has a larger diameter compared to a conventional lift beam. This increases the available space for lift cables hanging from the lift beam.