Abb Schweiz Ag

Olli Alkkiomäki

Teemu Tanila

Ville Särkimäki

Panagiotis Kakosimos

Joni Siimesjärvi

Kalle Suomela

Juha Alamäki

Disclosed is a method comprising obtaining a set of process data associated with an industrial process, wherein the set of process data includes measured values associated with the industrial process over a time period; estimating at least an energy consumption of each motor of a plurality motors over the time period based at least partly on the set of process data and a plurality of digital twins associated with the plurality of motors, wherein the plurality of digital twins includes at least a first digital twin of a first motor and a second digital twin of a second motor different to the first motor; extrapolating at least the energy consumption of each motor of the plurality of motors over an expected total useful lifetime of each motor; and indicating at least the extrapolated energy consumption of each motor of the plurality of motors.

Extrapolating motor energy consumption based on digital twin

An electric power train includes an electric drive, an electric motor driven by the electric drive, and a meshing pair of a drive gear and a driven gear. The drive gear is coupled to the electric motor and the driven gear is coupled to a mechanical load. The backlash of the meshing pair of the drive gear and the driven gear is measured and estimated based on a time until a contact of teeth of the rotating drive gear and the driven gear during a startup of the electric motor. Wear of the meshing pair of the drive gear and the driven gear based on a change in the measured backlash over time during the operation of the electric power train.

Monitoring a gear wear in an electric power train

To provide a status information also to one or more industrial devices for which no process data is available, a machine learning model is trained by using process data of a subset of industrial devices, corresponding product data, and statuses obtained by performing remote monitoring analysis to the process data. When user input including first information, which at least indicate at least one industrial device type is received, product data of one or more industrial automation devices, which are of the same indicated industrial device type is retrieved and inputted to the trained model, which outputs one or more estimated statuses.

Remote monitoring

Automated power conversion device operation and status data is received in a local terminal device. The operation and status data is forwarded from the local device to a remote device via a communications network. The remote device receives the operation and status data, and compares the received automated power conversion device operation and status data with automated power conversion device history data stored in a memory. Based on the comparing, the remote device generates a service recommendation for the automated power conversion device, Based on the generating, the remote device transmits the service recommendation to the local device via the communications network. The service recommendation is received in the local device. The local device displays the received service recommendation in to the user of the local device.

Communicating industrial device data in a communications system

A method comprises storing, in an automated power conversion device, operational information on the usage of the automated power conversion device, and information on user-adjustable parameter settings of the automated power conversion device. A local terminal device receives the operational information and the information on the user-adjustable parameter settings from the automated power conversion device, and forwards said information to a remote network node via a communications network. The received information is analyzed in the remote network node, and based on the analysis the remote network node generates a recommendation on an optimal set of user-adjustable parameters regarding the automated power conversion device. The generated recommendation is transmitted from the remote network node and received in the local terminal device.

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Helsinki, Finland

Olli Alkkiomäki